Quibim Precision

Mesa de trabajo 1Ictus


Stroke is a disease that occurs when a blood vessel that carries oxygen and nutrients to the brain is blocked by a clot or bursts. As the blood supply is diminished or interrupted, the affected region of the brain does not receive the necessary nutrients and its cells begin to die in minutes.


At present, stroke is a leading cause of death and disability worldwide, especially in low- and middle-income countries. In 2017, there was around 6.2 million of deaths and 132.1 million DALYs (Disability-Adjusted Life Year) due to this pathology. The burden of stroke is expected to increase in the coming years, both in terms of absolute numbers of incidents and deaths. This suggests that continuous monitoring of stroke burden is critical to informing healthcare delivery and resources.


There are two main causes of stroke: a blocked artery (ischemic stroke) or a leaking or bursting blood vessel (hemorrhagic stroke). Some patients may have only a temporary interruption of blood flow to the brain, known as a transient ischemic attack (TIA), which causes no lasting symptoms.

Ischemic stroke is the most common (approximately 87% of cases). It occurs when blood vessels in the brain become narrowed or blocked, causing a severe reduction in blood flow (ischemia). The blockage of these blood vessels is usually due to deposits of fat that accumulate in the blood vessels or by blood clots that travel through the bloodstream and lodge in the blood vessels of the brain. On the other hand, hemorrhagic strokes are caused by a weakened vessel that ruptures and bleeds into the surrounding brain. The blood collects and compresses the surrounding brain tissue. This vessel rupture may be due to uncontrolled high blood pressure, excessive treatment with anticoagulants, or trauma, among others.


In most cases, stroke is a disease that develops very quickly, causing a brain injury in a few minutes. The effects on the patient depend on several factors as the lesion location and the amount of brain tissue damaged. However, neurological complications such as the paralysis of one side of the body, speech issues, memory loss and erratic behaviors are common consequences of stroke incidents. A good guide for remembering the main symptoms of stroke can be remembered with the word FAST: Face, the face may have fallen on one side, the person may not be able to smile, or their mouth or eye may have fallen out; Arms, the person may not be able to raise both arms and keep them; Speech, the speech may be confused, or even not be able to speak at all or understand another person; Time, it is extremely important to call the emergency phone as soon as any of these symptoms are noticed. The Cincinnati Prehospital Stroke Scale (CPSS) is a system used to diagnose potential stroke patients in pre-hospital settings by evaluating their facial drop, arms drift and speech following the previous considerations.


Medical imaging plays a crucial role in the diagnosis and treatment of stroke patients, being Computed Tomography (CT) and Magnetic Resonance Imaging (MRI) the preferred modalities as they provide the highest discrimination of stroke lesions. Current guidelines for the emergency diagnosis of acute strokes are based on CT scanners due to its shorter acquisition time and higher availability. If imaging occurs within hours of stroke onset, it provides sufficient information to differentiate between ischemic and hemorrhagic stroke. MRI usually provides higher sensitivity and specificity in the diagnosis of acute ischemic stroke but is not typically available for emergency diagnosis.

The use of post-processing techniques can provide a range of quantitative image biomarkers to aid in the diagnosis and evaluation of stroke patients. Some of the most widespread tools for this purpose are the automatic identification and classification of stroke lesions by using Artificial Intelligence techniques, or the automatic segmentation of the stroke volume. These are very useful tools for emergency diagnosis since they allow reducing time and workload of health personnel in these situations where a rapid response is essential.

Other imaging post-processing tools can be very useful to evaluate brain integrity and its evolution over time, such as brain tractography and functional connectivity. Brain tractography reconstructs the white matter tracts and extracts metrics relating to the structural integrity of the tissue. On the other hand, functional connectivity allows the evaluation of functional integrity in the gray matter to identify those functional connections affected by the injury. These imaging biomarkers offer a guide to determine the degree of severity of the stroke lesion.

Risk factors

The risk factors for stroke are similar to those for coronary heart disease and other vascular pathologies: hypertension, elevated lipids, and diabetes. Risks due to lifestyle factors can also be addressed: smoking, lack of physical activity, unhealthy diet, and obesity. Combining these prevention strategies has been shown to be effective in reducing stroke incidence even in low-income countries.

The disease is more frequent in people over 55 years old and the risk is higher as age increases. The World Health Organization (WHO) estimates that in 2050 the population over 65 years will represent 46% of the population, of which approximately half may suffer a stroke. For this reason, early detection and monitoring of people at risk of suffering from this disease is very important for prevention and anticipation.


Once a stroke has occurred, treatment varies greatly depending on its type. The main treatment for ischemic stroke is intravenous tissue plasminogen activator (tPA) within 3 hours after stroke onset. The administration of tPA helps to restore blood flow to brain regions affected by a stroke, thereby limiting the risk of further damage and functional impairment. In the case of hemorrhagic strokes, the actions are focused on controlling the bleeding and reducing the pressure in the brain. Further surgery may be required to repair blood vessels. It is critical to make a correct diagnosis, since administering tPA to a patient suffering a hemorrhagic stroke has a high probability of causing further damage that may even lead to death.


  1. Krishnamurthi, R., Ikeda, T., & Feigin, V. (2020). Global, Regional and Country-Specific Burden of Ischaemic Stroke, Intracerebral Haemorrhage and Subarachnoid Haemorrhage: A Systematic Analysis of the Global Burden of Disease Study 2017. Neuroepidemiology, 54(Suppl. 2), 171-179.
  2. Global, Regional, and Country-Specific Lifetime Risks of Stroke, 1990 and 2016. (2018). New England Journal Of Medicine, 379(25), 2429-2437.
  3. O’Donnell, M., Chin, S., Rangarajan, S., Xavier, D., Liu, L., & Zhang, H. et al. (2016). Global and regional effects of potentially modifiable risk factors associated with acute stroke in 32 countries (INTERSTROKE): a case-control study. The Lancet, 388(10046), 761-775.
  4. O’Donnell, M., Xavier, D., Liu, L., Zhang, H., Chin, S., & Rao-Melacini, P. et al. (2010). Risk factors for ischaemic and intracerebral haemorrhagic stroke in 22 countries (the INTERSTROKE study): a case-control study. The Lancet, 376(9735), 112-123.
  5. Johnston, S., Mendis, S., & Mathers, C. (2009). Global variation in stroke burden and mortality: estimates from monitoring, surveillance, and modelling. The Lancet Neurology, 8(4), 345-354. doi: 10.1016/s1474-4422(09)70023-7
  6. Powers, W., Rabinstein, A., Ackerson, T., Adeoye, O., Bambakidis, N., & Becker, K. et al. (2018). 2018 Guidelines for the Early Management of Patients With Acute Ischemic Stroke: A Guideline for Healthcare Professionals From the American Heart Association/American Stroke Association. Stroke, 49(3).
  7. Puig J, Blasco G, Schlaug G, Stinear CM, Daunis-I-Estadella P, Biarnes C, Figueras J, Serena J, Hernández-Pérez M, Alberich-Bayarri A, Castellanos M, Liebeskind DS, Demchuk AM, Menon BK, Thomalla G, Nael K, Wintermark M, Pedraza S. Diffusion tensor imaging as a prognostic biomarker for motor recovery and rehabilitation after stroke. Neuroradiology. 2017 Apr;59(4):343-351.


World Osteoporosis Day (WOD) is here. This October 20th gives us an excellent opportunity to reflect on the millions of people affected by this disease, right? Well, yes and no.

Using WOD as a means of spreading the word and teaching about osteoporosis is a fantastic initiative of the International Osteoporosis Foundation (IOF). It will enlighten people who were previously oblivious to this disease and it will broaden the knowledge of those who knew about it, but thought it was just an unavoidable byproduct of aging. However, aging and osteoporosis are very serious multilayered matters. They should be focal concerns for all of us, not just during WOD, but each and every day.

Why? Well, for starters, let’s see what osteoporosis is and what are the effects of the disease in our bodies. Osteoporosis is a systemic bone disease characterized by the deterioration of the microarchitectural bone structure and by a low bone mass. This, of course, translates into brittle bones, which in turn greatly increase fracture risk. How great of an increase? More than 1.5 million fractures derived from osteoporosis are diagnosed annually. That means that in the minute it took you to read this section of the post, approximately 3 new fractures have been diagnosed. By the end of the day, more than 4,000 new fractures will have to be treated. Those patients with a severe degree of osteoporosis are risking a fracture just by sneezing. And I’m not making this up:

The IOF has launched a great website for World Osteoporosis Day, with this and lots of other resources that you’ll be able to share on social media to increase awareness about the disease and its consequences. Also, the World Health Organization (WHO) is hoping that 2020-2030 will be the decade of healthy aging and has launched the “Aging and Life Course” initiative, where osteoporosis is one of the main concerns.

We, and by we I’m referring to scientists, bioengineers, biotech companies, pharma companies, etc., should be doing our best not just to promote World Osteoporosis Day, but to use it as inspiration to create new technologies and drugs for diagnostic aid and treatment. For QUIBIM, musculoskeletal has been one of our main product lines since our beginnings, especially the trabecular bone characterization through magnetic resonance (MR) and computed tomography (CT). You can find a previous post describing the advantages of QUIBIM tools and how to use them here.

According to the IOF, more than 200 million people worldwide suffer from osteoporosis. That’s 200 million reasons to try to tackle this disease every day.

Image source: http://www.worldosteoporosisday.org/resources

Ángel Alberich-Bayarri, CEO de QUIBIM

La medtech valenciana QUIBIM cierra una ronda de inversión de 8 millones de euros

  • La inversión permitirá a QUIBIM ampliar la gama de algoritmos y componentes de alto valor disponibles a través de su plataforma de radiología basada en inteligencia artificial.

  • La startup permite la detección temprana del COVID-19 apoyando a los radiólogos a través de biomarcadores de imagen y la principal plataforma de IA para la detección del virus en Europa.

Valencia, España – 21 Julio 2020 – La compañía de tecnología médica (medtech) QUIBIM ha conseguido 8 millones de euros de financiación en una ronda de inversión coliderada por Amadeus Capital Partners y Adara Ventures, con la participación de Apex Ventures, Partech, Crista Galli Ventures, y los actuales accionistas, incluyendo TechTransfer UPV, fondo gestionado por Clave Capital, y Angels, sociedad de inversión del empresario Juan Roig.

QUIBIM está especializada en radiómica y en la extracción de información estandarizada y cuantitativa de imágenes médicas mediante la utilización de inteligencia artificial (IA). El postprocesamiento de imágenes médicas y la extracción de biomarcadores de imagen de QUIBIM permite a los hospitales y a las empresas farmacéuticas detectar enfermedades de forma temprana y sistemática.

La empresa ha llevado a mercado más de 20 algoritmos para un amplio conjunto de enfermedades como el cáncer, el Alzheimer, la artrosis y las enfermedades hepáticas. Recientemente ha lanzado un producto de radiografía de tórax y tomografía computarizada para detectar el COVID-19. QUIBIM Precision®, el nombre comercial de su plataforma, extrae y cuantifica biomarcadores específicos de enfermedades a partir de imágenes médicas con una elevada precisión. Sus productos se utilizan en más de 70 hospitales y 11 ensayos clínicos en todo el mundo, con 600.000 análisis y 6.5 millones de imágenes procesadas hasta la fecha.

QUIBIM fue fundada en 2012 por el Dr. Ángel Alberich-Bayarri y el Prof. Luis Marti-Bonmati, especialistas en imagen médica, que establecieron el proceso para el desarrollo de biomarcadores de imagen, adoptado en 2013 por la Sociedad Europea de Radiología (ESR) como el estándar oficial de la industria. En marzo de este 2020, QUIBIM se convirtió en la principal plataforma de IA para el estudio de COVID-19 en toda Europa. Poco después, la Sociedad Radiológica Norteamericana (RSNA), con más de 52.000 miembros de 153 países, se unió a la iniciativa con el objetivo de crear un repositorio médico mundial de casos de COVID-19, con el brazo europeo funcionando con QUIBIM Precision®.

Al incorporar tecnologías de IA, QUIBIM mejora la productividad y el flujo de trabajo de los servicios de radiología. La compañía está lanzando su familia de productos qp-Suites, diseñada para apoyar a los radiólogos centralizando las herramientas esenciales para el diagnóstico clínico en una única plataforma, aumentando así la eficiencia operativa.

Ángel Alberich, fundador y director general de QUIBIM, declara: “QUIBIM se encuentra en fase de expansión, creciendo internacionalmente mientras mantenemos la excelencia científica en el centro de nuestra misión. Esta ronda de financiación se utilizará para impulsar la plataforma de inteligencia artificial, nuestros algoritmos disponibles y los componentes de alto valor, para proporcionar una solución integral y única, apoyando a los sistemas sanitarios y a los proveedores de salud”.

“Nuestros nuevos inversores nos ayudarán a abrir oportunidades en nuevos mercados y contribuirán a fortalecer nuestra marca a nivel internacional. Podremos promocionar e impulsar comercialmente nuevas soluciones para la próstata, músculoesquelético y oncología y aumentar las ventas a nivel mundial, ampliando nuestra plantilla durante el próximo año”, añade.

Por su parte, Pierre Socha, socio de Amadeus Capital Partners, indica: “Estamos entusiasmados con el potencial de la radiómica para mejorar la detección de enfermedades y permitir tratamientos de precisión guiados por biomarcadores de imagen. La plataforma todo en uno de QUIBIM es la respuesta que los radiólogos han estado esperando y esperamos ayudarles a crecer internacionalmente mientras continúan la lucha contra el COVID-19 y otras enfermedades que amenazan la vida de las personas”.

“La rápida adopción de QUIBIM en el mercado es un indicador de cómo los clínicos e investigadores innovadores están muy interesados en el acceso y la explotación de la tecnología y los métodos de IA que pueden reconocer automáticamente patrones complejos en los datos de imagen médica, para obtener evaluaciones cuantitativas y mejorar el servicio que brindan”, concluye Rocío Pillado, socia de Adara Ventures.

La ronda de inversión de 8M€ ha sido asesorada legalmente por los despachos Garrigues (asesores legales de QUIBIM) y Araoz&Rueda.


QUIBIM es una compañía de tecnología médica (medtech) especializada en inteligencia artificial (IA) y tecnologías de procesamiento de imágenes aplicadas al desarrollo de biomarcadores de imagen en el campo de la radiología. La empresa dispone de una plataforma de software (QUIBIM Precision®) y algoritmos de IA para la extracción de biomarcadores de imagen cuantitativos. La plataforma se utiliza en hospitales, empresas farmacéuticas y centros de I+D.

La plataforma de análisis de imágenes QUIBIM Precision® ha recibido el marcado CE como Dispositivo Médico de Clase IIa, incluyendo los algoritmos de análisis de biomarcadores de imagen, el visor DICOM basado en web y la plataforma que alberga estos componentes y datos que se extraen de las imágenes médicas.

QUIBIM fue apoyada en 2015 por Lanzadera, la aceleradora de startups perteneciente a Marina de Empresas e impulsada por Juan Roig. Posteriormente, en 2017, recibió el soporte de Angels, la sociedad de inversión que forma parte del mismo hub de emprendimiento. Actualmente Angels mantiene en cartera un porcentaje minoritario de la compañía.

Sobre Amadeus Capital Partners

Amadeus Capital Partners es un inversor tecnológico global. Desde 1997, la empresa ha recaudado más de 1.000 millones de dólares para inversiones y los ha utilizado para respaldar a más de 150 empresas. Con una vasta experiencia y una gran red, el equipo de inversores y empresarios de Amadeus comparte la pasión por el poder transformador de la tecnología.

Entre las empresas pioneras que hemos respaldado se encuentran el proveedor de seguridad cibernética ForeScout (NASDAQ:FSCT); Graphcore, innovadores en microprocesadores inteligentes; la empresa de pruebas genéticas de fecundación in vitro Igenomix, IndiaMART, el mercado en línea B2B (NSE: INDIAMART) y la empresa de reconocimiento del habla VocalIQ (adquirida por Apple). Encuéntranos en https://amadeuscapital.com y @AmadeusCapital.

Sobre Adara Ventures

Fundada en 2005, Adara Ventures es una empresa de capital riesgo que gestiona más de 175 millones de euros de capital y se dedica a inversiones en empresas europeas de tecnología avanzada que se dirigen a los mercados empresariales (B2B). Adara invierte principalmente en las primeras etapas de desarrollo, con especial atención a la ciberseguridad, soluciones de datos/IA horizontales y verticales, computación en nube y software empresarial/industrial.Para más información, visita www.adaravp.com y síguenos en @Adaraventures.

 Sobre Apex Ventures

APEX Digital Health, el 2º fondo bajo el paraguas de APEX, invierte en empresas prometedoras del sector sanitario en su fase inicial.

APEX Ventures es una empresa europea de capital riesgo con sede en Viena y Frankfurt, centrada en empresas de alta tecnología. El equipo no sólo actúa como inversor, sino también como constructor de empresas con la misión de apoyar a los equipos de start-ups con más talento para la creación de líderes en el mercado mundial.

Sobre Partech

Con una cartera de casi 180 empresas repartidas en 30 países de Europa, Estados Unidos, África y Asia, Partech ha sido uno de los principales inversores internacionales que ha ayudado a fundadores visionarios durante casi 40 años. El equipo de Partech -compuesto tanto por antiguos empresarios como por ejecutivos de 15 países diferentes- aporta capital, experiencia, apoyo estratégico y redes a los empresarios en todas las fases de desarrollo: semilla, empresa y crecimiento. Con más de 1.500 millones de euros en gestión, Partech invierte de 200.000 a 50 millones de euros en tecnologías B2B y B2C que reconfiguran las industrias. Las empresas respaldadas por Partech han realizado más de 21 IPO’s y más de 50 transacciones estratégicas de fusiones y adquisiciones por valor de más de 100 millones de dólares.

Cartera actual de Partech: https://partechpartners.com/companies/

 Sobre Crista Galli Ventures

Crista Galli Ventures es un fondo de tecnología sanitaria que invierte en fase semilla y serie A. El fondo está respaldado por una family office de nacionalidad Danesa y tiene oficinas en Londres y Copenhague. Dirigido por la Dr. Fiona Pathiraja, Crista Galli Ventures es uno de los únicos fondos de tecnología sanitaria en el continente que tienen a un médico senior como socio y gerente. Las empresas de la cartera del fondo están distribuidas por Europa y Reino Unido, incluyendo empresas de deep-tech en radiología como contextflow y Smart Reporting.

Para más información:

















Ángel Alberich-Bayarri, CEO de QUIBIM

QUIBIM secures €8M for radiology AI platform that detects COVID-19 and other diseases early

  • Allows early detection of COVID-19 by radiologists through imaging biomarkers and is the main AI platform for screening for the virus across Europe

  • Investment will enable QUIBIM to expand range of algorithms and high-value components available through its AI-based radiology platform

Valencia, Spain – July 21, 2020 – Medtech company QUIBIM has closed €8M in new financing in a seed funding round co-led by Amadeus Capital Partners and Adara Ventures, with participation by Apex Ventures, Partech, Crista Galli Ventures and existing shareholders, including Tech Transfer UPV, managed by Clave Capital and Juan Roig.

QUIBIM specialises in radiomics, the extraction of standardised, quantitative information from medical imaging data sets using artificial intelligence (AI). QUIBIM’s medical image postprocessing and extraction of imaging biomarkers enables hospitals and pharmaceutical companies to detect diseases early and systematically.

QUIBIM has already launched more than 20 algorithms for a range of conditions including cancer, Alzheimer’s, osteoarthritis and liver disease. It has recently launched chest X-ray and CT scan products for COVID-19. QUIBIM Precision®, its proprietary platform, extracts and quantifies disease-specific biomarkers from medical images with ultra-high accuracy. Its products are used in over 70 hospitals and 11 clinical trials across the world, with 600,000 analyses and 6.5 million images processed to date.

QUIBIM was founded by Dr. Ángel Alberich-Bayarri and Prof. Luis Marti-Bonmati, two innovators at the forefront of medical imaging. They established the process for the development of biomarkers, adopted in 2013 by the European Society of Radiology (ESR) as the official industry standard. They again set a benchmark when, in March 2020, QUIBIM became the main AI platform for screening for COVID-19 across Europe. Shortly after, the Radiological Society of North America (RSNA), with more than 52,000 members from 153 countries, joined the initiative with the goal of creating a global medical repository of COVID-19 cases, with the European arm running on QUIBIM Precision®.

By incorporating AI technologies, QUIBIM also improves the performance and workflow of radiology departments. The company is launching its qp-Suites product family, designed to support radiologists by centralising the essential tools for clinical diagnosis in one platform, increasing operational efficiency.

Angel Alberich Bayarri, founder and CEO of QUIBIM, said, “QUIBIM is now at a scale-up point ready to grow internationally while maintaining great science at the core of our mission. This latest round of funding will be used to boost the AI platform, our available algorithms and high-value components, to provide a seamless, all-in-one solution supporting healthcare providers.” 

“Our new investors will open opportunities for us in new markets and help us to strengthen our brand internationally. We will be able to promote our new prostate, musculoskeletal and oncology solutions and increase sales globally, by expanding our workforce over the coming year.”

Pierre Socha, Partner, Amadeus Capital Partners, added: “We are excited by the potential of radiomics to improve disease detection and enable precision treatments guided by imaging biomarkers. QUIBIM’s all-in-one platform is the answer that radiologists have been waiting for and we look forward to helping them grow internationally while continuing the fight against COVID-19 and other life-threatening conditions.”

“QUIBIM’s rapid adoption is an indicator of how innovative doctors and researchers are eager to have access to and exploit AI technology and methods that can automatically recognise complex patterns in imaging data, to get quantitative assessments and improve the service they provide”, said Rocio Pillado, partner at Adara Ventures.

Legal advisers on the investment were Garrigues and Araoz&Rueda.


QUIBIM is a medtech company specialized in Artificial Intelligence (AI) and image processing technologies applied to the development of imaging biomarkers in the medical imaging field. The company has a proprietary software platform QUIBIM Precision® and AI algorithms for quantitative imaging biomarkers used by hospitals, pharmaceutical companies and R&D centres.

QUIBIM Precision® image analysis platform has received CE Mark certification as a Class IIa Medical Device, including its imaging biomarker analysis algorithms, the zero footprint DICOM viewer and its platform hosting these components and medical imaging data.

About Amadeus Capital Partners

Amadeus Capital Partners is a global technology investor. Since 1997, the firm has raised over $1bn for investment and used it to back over 150 companies. With vast experience and a great network, Amadeus’ team of investors and entrepreneurs share a passion for the transformative power of technology.

Pioneering businesses we’ve backed include cyber security vendor ForeScout (NASDAQ:FSCT); Graphcore, innovators in intelligent microprocessors; IVF genetic testing company, Igenomix, IndiaMART, the B2B online marketplace (NSE: INDIAMART) and speech recognition company VocalIQ (acquired by Apple). Find us at https://amadeuscapital.com and @AmadeusCapital.

About Adara Ventures

Founded in 2005, Adara Ventures is a Venture Capital firm managing over €175 million in capital and dedicated to investments in European Deep Tech companies addressing enterprise (B2B) markets. Adara invests primarily in the early stages of development with a particular focus on Cybersecurity, Horizontal and Vertical Data/AI solutions, Cloud computing, and Enterprise/Industrial software. For more information, visit www.adaravp.com and follow us @Adaraventures.

 About Apex Ventures

APEX Digital Health, the 2nd fund under the APEX umbrella, invests in promising early-stage companies in the healthcare sector. APEX Ventures is a European venture capital firm with headquarters in Vienna and Frankfurt, focusing on deep-tech companies. The team is not only acting as investors but also as company builders with a mission to support the most talented start-up teams in building global market leaders.

About Partech

With a portfolio of almost 180 companies spread across 30 countries in Europe, the US, Africa, and Asia, Partech has been one of the leading international investors helping visionary founders for almost 40 years. The Partech team – made up of both former entrepreneurs and executives from 15 different countries – brings capital, experience, strategic support, and networks to entrepreneurs at every stage of development: seed, venture, and growth. With over €1.5B under management, Partech invests from €200K to €50M in B2B and B2C technologies reshaping industries. Companies backed by Partech have completed more than 21 IPOs and more than 50 strategic M&A transactions valued over $100M.

See Partech’s current portfolio: https://partechpartners.com/companies/

 About Crista Galli Ventures

Crista Galli Ventures is an evergreen healthtech fund, investing at seed and series A. The fund is backed by a Danish Family office and has offices in London and Copenhagen. Led by Dr. Fiona Pathiraja, Crista Galli Ventures is one of the only healthtech funds on the continent to have a senior physician as managing partner. The firm’s portfolio companies are based across Europe and the UK, including deep-tech radiology companies contextflow and SmartReporting.

More information:



We are hiring a PROJECT MANAGER – R&D Engineer

QUIBIM is now hiring a highly motivated researcher to join our R&D Team in Valencia, with a strong background on the latest medical imaging and AI technologies for imaging biomarkers analysis. He/She will be dedicated to the development of a modular platform based on a plug-in software architecture of prostate imaging quantitative analysis. In addition to this, the candidate will have the opportunity to participate and further develop his/her research career within the framework of R&D projects QUIBIM is part of. This includes world-leading projects in COVID-19 and AI applied to Medical Imaging diagnosis on a variety of diseases (Brain & Stroke; Oncology and Musculoskeletal). This position is intended to be permanent and further professional development, responsibilities and benefits are expected after the 1-2 year.

Main job duties and responsibilities

  • Lead the R&D strategy for qp-Prostate Solution. Development of a modular platform based on a plug-in software architecture of prostate imaging quantitative analysis
  • Integration of new analysis methodologies. 
  • Participation in all Research Projects that QUIBIM is involved in. 
  • Oversee all algorithms design and changes in QUIBIM products.
  • Keep abreast of new trends and best practices in the technology AI and Medical Image sector. 
  • Take the initiative in thought leadership, innovation and creativity. 
  • Work closely with CEO, R&D Manager, Clinical Trials Division Manager and CTO to define and deliver new products and enhancements. 

Requirements/ Preferred qualifications

  • Computer Science / Technology / Medical sciences: PhD or equivalent 
  • PhD in Telecommunication Engineering and/or Biomedical Engineering. 
  • Research experience in data images processing and imaging biomarkers. 
  • Knowledge of techniques of high-resolution magnetic resonance images. 
  • Prior experience in medical imaging processing. 
  • Knowledge of cloud technologies. 
  • At time of recruitment, applicants must have not resided or carry out his/her main activity (work, studies, etc.) in Spain for more than 12 months in the 3 years immediately before the job starting date. Short stays such as holidays are not taken into account. 
  • Hands-on experience with complex project management.
  • Experience on Image Analysis companies is a plus. 
  • IT Knowledge: Python, MATLAB, C++, MongoDB, Azure, Node, Angular. 
  • Advanced level of English with oral fluency.
  • Highly analytical, detail-oriented and a strong sense of business acumen: you have a track record of managing new ideas and creative solutions.
  • Ability to manage and prioritize your workload in a fast-paced, high-growth, occasionally ambiguous environment. 
  • Proactive problem solver and critical thinking. 
  • Attention to details.
  • Integrity. 
  • Responsibility, leading the solution to challenges

If you are proactive, dynamic and forward-thinking profile Apply Here

Recurso 2

ImagingCovid19AI.eu now an international initiative

These are difficult times, it is clear that this COVID19 pandemic that is assailing the world is going to change our way of life. It is time to be united and to collaborate, where doctors, researchers, mathematicians, physicists and the entire scientific community unites to fight the COVID-19 virus by sharing our knowledge and research.

After opening up free access to our QUIBIM Precision – COVID19 platform and AI algorithms to the scientific community to find new diagnostic tools and ways to understand the mechanisms and aggressiveness of the disease, we co-founded the Imaging COVID-19 AI initiative, a multicenter European project to enhance computed tomography (CT) in the diagnosis of COVID-19 by using artificial intelligence. QUIBIM_AI_COVID19

This collaborative initiative coordinated by the Netherlands Cancer Institute, together with Rovobision, the European Society of Medical Imaging Informatics (EuSoMII) and QUIBIM, has had a great response with the participation of several hospitals, radiology centres and research groups from across the world including Italy, Spain, Netherlands, India, and Korea among others.

Furthermore, last March 30th the Radiological Society of North America (RSNA) announced (press release) its willingness to join this initiative. We are proud to welcome our partnering with this renowned society by joining the Imaging COVID-19 AI initiative to spread it throughout the medical imaging community around the world.

“The organizations expressed the common goal of creating a secure way to share COVID-19 imaging, in order to assess lung involvement more accurately with AI. They will collaborate to enable hospitals to provide imaging data securely and efficiently with researchers, respecting privacy and ethical principles. They will define and publish protocols for selecting and labeling imaging data associated with COVID-19 as a tool for researchers and practitioners. Other interested organizations are invited to join this coalition to share information and facilitate a rapid response to COVID-19.” the Radiological Society of North America declares in the press release issued on March 30th, 2020.

Fighting COVID19 through AI

This initiative for automated diagnosis and quantitative analysis of COVID-19 will create a deep learning model for automated detection and classification of COVID-19 on CT scans. This model will also be used for assessing disease severity in patients by quantification of lung involvement to rapidly develop an artificial intelligence solution.

The number of people affected by COVID-19 is increasing every day with healthcare systems across the world on the verge of collapsing, which is why QUIBIM took part in this initiative to develop a tool to support doctors against this virus. As the initiative states “automated image analysis with artificial intelligence techniques has the potential to optimize the role of CT in the assessment of COVID-19 by allowing accurate and fast diagnosis of infection in a large number of patients. AI has the potential to support clinical decision making and improve workflow efficiency.”

Our role in the initiative

As a company specialized in machine learning and image processing technologies for medical images, QUIBIM provides to the initiative the research platform QUIBIM Precision for development and deployment of the deep learning model. The data will be transferred directly and securely from each participating hospital to the servers of the company. The QUIBIM platform, as well as other software utilities to upload images and clinical information provided, enforces a role-based authentication mechanism which guarantees that Study Data remain protected and only available to authorized users.

In that sense, QUIBIM places at the service of the project its experience on interconnectivity with hospitals and sending images through its tool MIUC (Medical Imaging Universal Connector) following all regulations of GDPR, anonymization and personal data processing.

Visit Imaging COVID-19 AI initiative site – LINK



Lung texture outcomes in Chest Xray

Imaging, AI and radiomics to understand and fight coronavirus Covid-19

  • There is currently no effective cure for this virus and there is an urgent need to increase global knowledge in its mechanisms of infection, lung parenchyma damage distribution and associated patterns.
  • Artificial Intelligence and radiomics applied to X-Ray and Computed Tomography are useful tools in the detection and follow-up of the disease.

In December 2019 the city of Wuhan (China) became the center of a pneumonia outbreak of an unknown cause with global implications. In early 2020, Chinese scientists isolated a novel coronavirus (CoV), from patients in Wuhan, formerly  known as 2019-nCoV 1 and now renamed as Covid-19 by the World Health Organization (WHO). Patients infected with this strain present a wide range of symptoms 2, most seem to have mild disease, with about 20% appear to progress to severe disease, including pneumonia, respiratory failure and in around 2% of cases death 3. Common signs of infection include respiratory symptoms, shortness of breath and breathing difficulties, fever and cough 4.

Coronaviruses (CoV) are a large family of viruses that cause illness ranging from the common cold to more severe diseases such as Middle East Respiratory Syndrome (MERS-CoV) and Severe Acute Respiratory Syndrome (SARS-CoV). This novel coronavirus (nCoV) is a new strain not previously identified in humans. Although this outbreak had its start in China, today there are several countries around the world with identified cases, making it a worldwide public health concern.

Confirmed cases of COVID-19 acute respiratory disease reported by provinces, regions and cities in China, 13 February 2020*

Table 1. Confirmed cases of COVID-19 acute respiratory disease reported by provinces, regions and cities in China, 13 February 2020*

How could AI and imaging biomarkers aid to fight against this emerging zoonotic illness?

There is currently no effective cure for this virus and there is an urgent need to increase global knowledge in its mechanisms of infection, lung parenchyma damage distribution and associated patterns, not only for disease detection or to complement the diagnosis, but also to support the design of a curative therapy. AI and radiomics applied to X-Ray and Computed Tomography are useful tools in the detection and follow-up of the disease. As stated in 5, conspicuous ground grass opacity lesions in the peripheral and posterior lungs on CT images are indicative of Covid-19 pneumonia. Therefore, CT can play an important role in the diagnosis of Covid-19 as an advanced imaging evidence once findings in chest radiographs are indicative of coronavirus. AI algorithms and radiomics features derived from Chest X-rays would be of huge help to undertake massive screening programs that could take place in any country with access to X-ray equipment and aid in the diagnosis of Covid-19 6.


FIGURE 1: QUIBIM – Quantitative Structured Report – Chest X-Ray Classifier

In order to speed up the discovery of disease mechanisms, QUIBIM’s Chest X-Ray Classifier (Figure 1) can be used to detect abnormalities and extract textural features of the altered lung parenchima that could be related to specific signatures of the Covid-19 virus. We have combined all our knowledge in AI and radiomics in this novel analysis pipeline specifically designed to extract disease patterns. First, the Chest X-Ray is automatically analyzed using a deep learning classifier to provide an abnormality score between 0 and 1. Any abnormality score above 0.3 is considered as an abnormal case. After this initial analysis, lungs are automatically segmented using a Mask R-CNN like convolutional neural network architecture and finally, a massive extraction of texture features is applied (figure header). This pipeline has been completely automated and will serve to provide additional information to the diagnosis of Covid-19.

QUIBIM is committed to provide access to our existing AI technology to find new diagnostic tools and ways to understand the mechanisms and aggressiveness of the disease, contributing to the efforts to find a cure.  Any clinician can fill this form created by QUIBIM to get free credentials for the use of the AI Chest X-Ray classification analysis technology available in the QUIBIM Precision Cloud platform. This research tool is offered to any doctor worldwide with the need of analyzing Chest X-Rays with suspicion of Covid-19.


  1. https://reference.medscape.com/slideshow/2019-novel-coronavirus-6012559
  2. https://www.ncbi.nlm.nih.gov/pubmed/31978945
  3. https://www.who.int/docs/default-source/coronaviruse/situation-reports/20200128-sitrep-8-ncov-cleared.pdf
  4. https://www.who.int/health-topics/coronavirus
  5. https://pubs.rsna.org/doi/10.1148/radiol.2020200274
  6. https://www.auntminnie.com/index.aspx?sec=sup&sub=xra&pag=dis&ItemID=127983



Rafael López González – R&D Engineer



QUIBIM Brings AI to Radiology Workflows with NVIDIA EGX

Artificial intelligence is becoming a reality in radiology as new AI solutions are moving from research to clinical validation and daily clinical workflow.

QUIBIM (Valencia, Spain) has a proprietary software platform and develops AI algorithms across imaging modalities for quantitative imaging biomarkers used in hospitals, radiology centers and clinical trials focusing on body ( liver, prostate) and musculoskeletal analysis algorithms.

QUIBIM’s solutions have already demonstrated a major impact in partner hospitals and radiology centers with a 70% reduction in reporting time of multiple sclerosis cases of the brain using QUIBIM’s White Matter Lesions algorithm. In addition, a large hospital in Valencia, Spain, has experienced significant cost savings using QUIBIM’s Chest X-ray classifier product.

By being able to seamlessly integrate AI solutions in the radiology workflows, QUIBIM helps healthcare providers stay ahead of increasing amounts of data needed for patient care. For example: with the QUIBIM Precision® data mining tool, it is possible to obtain new disease phenotypes based on non-supervised AI clustering. The combined power of AI and edge computing can retain critical processing tasks on devices at the point of care to help in earlier diagnosis of disease and eliminating manual tasks of the radiologists, thereby enabling them to optimize reporting and interpretation.

QUIBIM Precision® and NVIDIA EGX

Delivering AI at the edge minimizes data privacy concerns and enables real-time AI for clinical decisions. QUIBIM and NVIDIA are bringing AI to the edge of medical imaging, the most important healthcare tool in early detection, with the NVIDIA EGX Intelligent Edge Computing Platform. Having the possibility to containerize algorithms on NGC, which is optimized on EGX systems, QUIBIM is able to expand its reach, which helps in the democratization of AI and the ability to provide access to care using AI even in the remote regions of the world.

By delivering new diagnostic and operational capabilities that enhance patient care, QUIBIM and NVIDIA EGX are ushering in a new generation of smart hospitals and radiology departments.

RSNA 2019

with new features!

For the third consecutive year, and coinciding with our business expansion, currently installed in more than 60 hospitals and used by more than 20 clinical trials worldwide, QUIBIM attends this RSNA 2019 edition with new solutions based on artificial intelligence.

Located at the AI Showcase booth #10418, QUIBIM has set up three demo points where participants can interact and navigate the platform testing their main features:

  • AI app’s for quantitative analysis and workflow optimization
  • Radiomics Data Miner tool.
  • Quantitative and radiological structured reporting.
  • Vendor-agnostic system compatible with all PACS vendors and equipment manufacturers.
  • Head-to toe solution (neurology, chest, body, and musculoskeletal).
  • Advanced visualization tools: Zero-footprint DICOM viewer. 


Seamless AI for Radiologists

QUIBIM Precision® platform integrates AI algorithms into the radiology department workflow with no clicks, making it an efficient system that provides a complete radiology solution covering the AI and quantitative needs.

In our strategy of providing value-driven solutions, QUIBIM uses AI as a tool for organ segmentation (prostate, liver, vertebraes, fat) using Deep Learning, lesions detection (white matter lesions), and classification (chest X-ray). These AI solutions are seamlessly integrated with PACS and RIS making them a part of daily clinical practice, by activating smart back-end rules engine to schedule post-processing tasks.

Discover how QUIBIM empowers radiologists’ workflow at booth #10418 – AI Showcase in the North Hall Level 2.

RSNA_schedule a meeting

In addition, as an advanced research tool QUIBIM has integrated a prostate nosological imaging module based on a non-supervised AI algorithm using quantitative data obtained from multiparametric magnetic resonance (mp-MR) images. This method could serve as a pipeline for the development of nosologic maps and speed up the case assessment and reporting time. This tool helps radiologists’ daily work leading them focus on small zones with malignant features that would be undetected in most of the cases.

More at RSNA 2019


Discover at the AI Theater our presentation AI Integrated in Daily Workflow with QUIBIM Precision: Visualize, Annotate, Quantify, Report and Discover how QUIBIM Precision® is providing a seamless solution for AI in radiology, with a complete integration in clinical routine and a completely automated rules engine to get all results before reporting. Special analysis modules for brain, musculoskeletal, lung and body-oncology applications. Presented by Angel Alberich-Bayarri, PhD, our CEO and Founder.

Monday 12:00-12:20 PM | AI24 | Room: AI Showcase, North Building, Level 2.  ADD TO YOUR CALENDAR


Also, we have organized a special workshop for those interested in a Head-to-Toe Hands-on with AI and Imaging Biomarkers Integrated in PACS. QUIBIM Precision. We will show how to empower radiologists’ daily practice by offering full control over our AI solutions. We will show how AI solutions are seamlessly integrated with PACS and RIS on a daily practice and how to interpret quantitative imaging and AI results.  Presented by Angel Alberich-Bayarri, PhD | Fabio Garcia-Castro | Mar Roca-Sogorb, PhD

Tuesday 1:00-2:30 PM | HW32 | Room: AI Showcase, North Building, Level 2


Register now

In order to get the best experience for this workshop, it is highly recommended that attendees bring a laptop with a keyboard and decent-sized screen.

Join us at RSNA 2019!





Next 18th and 19th October 2019, Valencia will host the Annual Meeting of the EUSOMII society (AMI2019). The society has planned a two days congress combining educational and scientific sessions in the field of medical imaging informatics.

In this edition, QUIBIM will participate with 2 lectures, 3 oral communications, 7 posters and a QUIBIM Precision exhibit space for all those interested in our artificial intelligence algorithms and imaging biomarkers solutions. If you want to book a demo, do not hesitate and book a timeslot!

Book a DEMO

As a board member of EUSOMII, it is an honor to bring to Valencia, our city, such an interesting program. Holding this meeting in an innovative environment like the Hospital Universitario y Politécnico La Fe de Valencia is a sign of the change that healthcare is experiencing nowadays” explained Ángel Alberich-Bayarri, CEO & Founder of QUIBIM and Chair Industry and Startup Committee of EUSOMII.

Check out our participations at AMI 2019:

FRIDAY, October 18th 2019

  • Keynote Lecture I – Imaging biomarkers and radiomics: source of big data for AI – Dr. Luis Martí-Bonmatí

SATURDAY, October 19th, 2019

  • Didactic Lecture II-III – Imaging Biomarkers – Dr. Angel Alberich-Bayarri
  • Oral Communication – Image analysis using an intercontinental infrastructure for the deployment of
    trustworthy cloud services: the ATMOSPHERE project. Authors: Ignacio Blanquer, Eduardo Camacho-Ramos, Andrey Brito, Ana Jimenez-Pastor, Christof Fetzer, Altigran da Silva, Amanda Calatrava, Fabio García-Castro, Ángel Alberich- Bayarri, Franciso Brasileiro.
  • Oral Communication – Quantification and evaluation of pre-post exercise femoral cartilage thickness and T2
    changes in ultramarathon athletes. Authors: Fabio García-Castro, Jordi Catalá March, Daniel Brotons Cuixat, Miquel Llobet Llambrich, Eduard Sánchez Osorio, Ángel Alberich-Bayarri.
  • Oral Communication – Automated Lung Segmentation in Chest Radiographs using Deeply Supervised Convolutional Neural Networks Trained by means of a Database Augmented with a Generative Adversarial
    Authors: Rafael López.


  1. Automatic cartilage segmentation in 3D T2w high resolution MR using a Deeply
    Supervised Multi-Planar Convolutional Neural Network. Authors: Ana Jimenez-Pastor, Fabio García-Castro, Ángel Alberich-Bayarri, Luis Marti- Bonmati.
  2. Automatic quantification of white hyperintensities in a healthy aging cohort using
    Convolutional Neural Networks. Authors: Ana Jimenez-Pastor, Eduardo Camacho-Ramos, Ángel Alberich-Bayarri, Carles Biarnes, Josep Garre, Joan Carles Vilanova, Rafel Ramos, Reinald Pamplona, Salvador Pedraza, Josep Puig.
  3. Adaptation of TLAP-certified radiological structured reports to be used in a cloud
    platform environment. Authors: Fernando Bacha-Villamide, Eduardo Camacho-Ramos, Alejandro Mañas-Garcia, Luis Martí-Bonmatí, Angel Alberich-Bayarri.
  4. Development and validation of an inter and intra-sequence registration algorithm in
    multiparametric prostate resonance imaging. Authors: Matías Fernández, Mar Roca-Sogorb, Fabio García-Castro, Raúl Yébana, María Asunción Torregrosa, Leonardo Bittencourt, Margarita García Fontes, Paula Pelechano, Luis Martí- Bonmatí, Ángel Alberich-Bayarri.
  5. Computer aided diagnosis for Rheumatic Heart Disease by AI applied to features
    extraction from echocardiography. Authors: Eduardo Camacho-Ramos, Ana Jimenez-Pastor, Ignacio Blanquer, Fabio García- Castro, Ángel Alberich-Bayarri.
  6. Outcome prediction after acute stroke through functional magnetic resonance imaging. Authors: Eduardo Camacho-Ramos, Ana Jimenez-Pastor, Carles Biarnes, Ángel Alberich-Bayarri, Salvador Pedraza, Josep Puig.
  7. Implementation of an interactive radiological structured report management system
    with AI annotation capabilities. Authors: Alejandro Mañas-Garcia, Eduardo Camacho-Ramos, Ismael Gonzalez, Fernando Bacha, Ángel Alberich-Bayarri, Luis Marti-Bonmati.

Our Quibimers are already heating engines for AMI2019. We look forward to meeting you!