Congress

RSNA 2019

QUIBIM at 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. 

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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.

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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

AI THEATER PRESENTATION

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

AI WORKSHOP

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

Interested?  PLACES ARE LIMITED!

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!

 

 

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QUIBIM HOSTING EUSOMII ANNUAL MEETING 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.

POSTERS:

  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!

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QUIBIM at the annual Outsourcing in Clinical Trials Europe 2019

We are very happy to share with you QUIBIM´s experience at the last Outsourcing in Clinical Trials Europe 2019 from 14th to 15th of May in Milan (Italy).

Clinical Trials Manager and Chief Strategy Officer, Irene Mayorga and Kabir Mahajan, joined this annual meeting to introduce the services that QUIBIM offers to CRO’s and pharmaceutical companies conducting imaging clinical trials. They had the pleasure of interacting with many novel drug development companies & CRO’s focusing on glioblastoma, pancreatic cancer, other cancers and diffused liver disease and had the chance to show QUIBIM´s experience on this front.

Also, we had the opportunity to discuss QUIBIM´s services as an imaging core lab, not only with the scientific and technical aspects, but also with the design and development of imaging documentation such as the imaging trial charter, the medical imaging validation and imaging acquisition quality control,  statistical analysis and other standard clinical trials management services.

If you did not have the chance to join us in Milan, you can meet Irene Mayorga Ruiz and Kabir Mahajan at the BIO Convention in Philadelphia from June 3- June 6, 2019 where they would be showing the latest developments in the QUIBIM Precision platform for managing clinical trials. You can use the following link to book a demo.

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Comprehensive solutions will boost AI use in medical imaging

Integrating artificial intelligence (AI) into the radiologist’s workflow is still challenging, but all-inclusive solutions can help unfold algorithms’ power, QUIBIM CEO and founder Angel Alberich-Bayarri explained during the ESR AI Premium Event, which was hosted by the European Society of Radiology (ESR) and the European School of Radiology (ESOR) earlier this month in Barcelona.

Medical imaging AI is a bubbling field but very few solutions are used in daily practice today, Alberich told delegates during the busy meeting, which gathered top researchers in medical imaging AI and thousands of online attendees. “We have a lot of research, AI algorithms and start-ups, but few are really embedded in the radiology workflow,” he said.

A main obstacle to AI integration is a lack of knowledge of utilities. For most imaging biomarkers, the real application relationship with clinical endpoints on a large scale – diagnostic, prognostic and treatment response – remains unknown. Clinicians don’t want to integrate biomarkers that have not been validated, but if they don’t gather information massively and try to understand how biomarkers relate to the disease, they will never help advance healthcare, Alberich explained.

“We have to change our minds and not wait for biomarkers to be validated before they can be extracted on a daily basis. Similarly to genomics: we have to do sequencing and study diseases to detect unknown mutations by ourselves,” he said.

The lack of annotated data is another challenge. Radiology reports are not filled with a focus on data annotation, but on descriptive language that needs to be processed by natural language processing (NLP). However they would be an ideal source of knowledge, and not just for the clinicians.

One-stop-shop platform using biomarkers

QUIBIM was created in 2015 as a spinoff company of La Fe Hospital in Valencia, Spain, to help radiologists make the most of AI in their everyday practice, by providing a one-stop-shop solution using imaging biomarkers and powerful algorithms.

“Offering a single solution embedded in workflows is key because radiologists will not buy all start-up micro developments but the best platform,” he said.

The very name of the company is an acronym and stands for Quantitative Imaging Biomarkers in Medicine. Imaging biomarkers enable to measure everything happening in the body to extract parameters that can provide information on the tissue of the lesion type beyond classification. Fuelled by AI, these biomarkers can deliver unprecedented information on disease.

“Many different imaging pipelines have dramatically changed thanks to AI integration. For example, we used to have lots of problems doing segmentation with traditional algorithms in tissues and organs such as the liver in MRI. Thanks to AI, segmentation has improved and with it our knowledge of liver disease,” he said.

A prerequisite is to integrate data mining solutions to make radiomics easy to everyone. This means it must be embedded in the same platform, as current solutions are not able to treat this amount of quantitative data from patient cohorts. “A lot of parameters are quantified in daily routine, but there is still no way to store and process them massively. Our current PACS systems are simply not prepared for quantitative data,” Alberich said.

There is a lot of sense in working within a structured report (SR), as it enables to annotate data that will further advance research. Prospectively the studies can be very well annotated if AI imaging biomarkers are integrated in the fields of the SR. Working with the SR would tremendously facilitate communication between clinicians and with patients.

“We are building the radiology report of the future, only we’re doing it now. Patients do not understand radiology reports, so we have to change the way we communicate. We are very much aligned with the standardized way blood test findings are reported, everyone understands whether findings are in or out of range and if there is any abnormality. We have to be more intuitive in our communication,” Alberich said.

QUIBIM is developing quantitative, one-page long structured reports that are actionable, quantitative and automated. The reports are designed with KOLs in each speciality, to make sure they reflect the reality of clinical practice.

Clinical input and powerful technology

Cooperation with clinicians is a key axis for the company, which uses a stepwise model to create new solutions with clinicians in the loop.

The company develops highly performing AI algorithms using unprecedented network architectures, for instance, multiscale convolutional networks ensemble in brain MR, 2.5D network in liver MR and referee network in chest x-ray, and hundreds of thousands of annotated images that have been acquired through cooperation with researchers and university hospitals.

QUIBIM has launched algorithms in different product areas to provide a head to toe imaging biomarker solution; in neuro for Alzheimer, ALS, MS, stroke and cerebrovascular events; in MSK for articulations; in chest for screening, COPD and fibrosis; and in breast for screening. More products will soon be released that will focus on other body areas.

More than 60 hospitals worldwide currently use QUIBIM tools, most of which have received CE marks and/or are FDA pending. The company has notably developed the new ESOR teaching platform and has supplied its QUIBIM Precision® image analysis platform to the AI Precision Health Institute at the University of Hawai‘i Cancer Center in Honolulu. QUIBIM has received €3.5m funding ever since its creation and has offices in Spain and the U.S.

QUIBIM TEAM ECR 2019

ECR 2019 sets the trend in Artificial Intelligence

The city of Vienna was at the real core of Medical Imaging and AI at the 25th European Congress of Radiology (ECR). At QUIBIM we always enjoy being at this annual meeting because it is the perfect combination of a science and industry exhibition. In this edition, the congress reached the milestone of 30,000 attendees, and the numbers are expected to go up with each year.

QUIBIM was glad to be participating in both, the scientific and industry sessions. Our oral presentations were mainly addressing current challenges of artificial intelligence (AI) and convolutional neural networks (CNN) in clinical needs like metabolic disorder, prostate cancer and osteoarthritis. Ana Jiménez-Pastor, Rafael López-González and Fabio García-Castro, R&D Engineers at QUIBIM presented our new research in image processing pipelines aiming to perform a virtual dissection of the organs through an automated segmentation combined with features extraction.

Personally,  I was happy to give 3 lectures focused on the future of radiology: 3D Post-processing in 2019, Deep Learning in Medical Imaging and Start-up in Radiology. In the 3D Post-processing lecture I introduced, what I think is the main revolution of AI in our field the concept of Virtual In-Vivo Dissection (VIVID), a name coined by my team and I at QUIBIM, which is a strategy of isolating human body organs in medical images for  characterization through features such as imaging biomarkers. This has several applications, challenges and is difficult to solve by traditional computer vision algorithms like liver or cartilage segmentation in Magnetic Resonance Imaging but it has become a reality thanks to the use of CNN architectures such as U-Net combined with deep supervision. In the Deep Learning in Medical Imaging session, I  focused on using other presentation formats and I was glad to give a TED talk and share the podium with Dr. Wiro Niessen, who spoke about Machine Learning in a Pecha Kucha format. This session was organized by the European School of Radiology (ESOR) and was chaired by Prof. Dr. Valérie Vilgrain, and I must say the atmosphere was excellent and the room was really packed! Finally, in a session chaired by Prof. Dr. Elmar Kotter,  we shared our insights on how to create a start-up company in Radiology from scratch, how to get funding from investors and the main considerations when scaling-up.

QUIBIM was also invited by the ECR to give a presentation within the Artificial Intelligence Exhibition (AIX) sessions, a new space for innovative AI companies. During this session, moderated by Dr Hugh Harvey and Dr Wim Van Hecke, we presented the newest version of the QUIBIM Precision V3.0 platform launched at the last RSNA 2018.

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Meet us at ECR 2019

We are delighted to share that QUIBIM will attend the 25th European Congress of Radiology 2019 (ECR) from Wednesday, February 27th to Sunday, March 3rd, 2019. This year we have changed our standard location, now you can meet us at the AI Exhibition area (EXPO X1) booth #AI-15.

ECR attendees will have the opportunity to explore our latest version of the platform QUIBIM Precision® V3.0, focused on the Symbiosis of Radiology and Artificial Intelligence to seamlessly integrate imaging biomarkers into radiology workflows. Come and try our AI solutions and imaging biomarkers analysis!

Book a DEMO

Make sure not to miss our scientific contributions:

  • Wednesday, February 27:
    • 3D post-processing in 2019 – Dr. Ángel Alberich Bayarri.   |  Imaging Informatics, Artificial Intelligence and Machine Learning (Room N) – 16:00 – 17:30
    • Deeply supervised networks for the automated liver segmentation and quantification on MECSE-MRI – Ana Jiménez Pastor | EPOS
    • Stress testing a deep learning algorithm for normal/abnormal classification of Chest X-rays on a spectrum-biased abnormal – Rafael López Gónzalez  |  EPOS
      weighted dataset.
  • Thursday, February 28:
    • Functional imaging of the liver Chairperson’s introduction – Dr. Luis Martí Bonmatí. |  Abdominal Viscera, Contrast Media (Room M 5) – 10:30 – 12:00
    • AI PITCH – Dr. Ángel Alberich Bayarri.  |  Artificial Intelligence Exhibition (AIX) Theatre ( AIX Theatre) – 11:40
    • What to think about when writing a paper – Dr. Luis Martí Bonmatí. |  Education, General Radiology, Professional Issues (Room: C&T 3) – 14:00 – 15:00
    • Deep learning (DL) in medical imaging – Dr. Ángel Alberich Bayarri.   |  Education, General Radiology, Artificial Intelligence and Machine Learning (Room: M3) – 14:00 – 15:30
    • Quantification and evaluation of pre-post exercise femoral cartilage thickness and T2 changes in ultramarathon athletes – Fabio García Castro  |  Musculoskeletal, Imaging Methods (Room: O) – 14:00 – 15:30
    • How to manage critical reviews – Dr. Luis Martí Bonmatí. |  Education, General Radiology, Professional Issues (Room C&T 3) – 15:00 – 16:00
  • Friday, March 1:
    • ECR Academies: Radiology Leaders’ Bootcamp: Dream team Chairperson’s introduction –Dr. Luis Martí Bonmatí. |  Management/Leadership (Room M 2) – 10:30 – 12:00
    • Start-up in radiology – Dr. Ángel Alberich Bayarri.   |  Management/Leadership (Room M2) –  14:00 – 15:30
  • Saturday, March 2:
    • Automated Prostate multiregional segmentation in Magnetic Resonance using deeply supervised Convolutional Neural Networks – Rafael López González  |  Artificial Intelligence and Machine Learning, Oncologic Imaging, Imaging Informatics, Genitourinary, Physics in Medical Imaging (Room G) – 16:00 – 17:30
  • Sunday, March 3:
    • Automatic visceral fat characterization on CT scans through Deep Learning and CNN for the assessment of metabolic syndrome –  Ana Jiménez Pastor | Artificial Intelligence and Machine Learning, Abdominal Viscera, GI Tract, Oncologic Imaging, Imaging Informatics (Room D) – 14:00 – 15:30
    • Liver Case-Based Diagnosis Training – Dr. Luis Martí Bonmatí. |  Education, General Radiology, General Radiography (Radiographers) (Room E1) – 13:00 – 15:30

Join us at ECR 2019!

 For more information, get in touch with us at contact@quibim.com

QUIBIM_Symbiosis of Radiology and AI

QUIBIM at RSNA 2018!

We are happy to announce that QUIBIM will be attending this year’s annual meeting of the Radiological Society of North America – RSNA 2018. From November 25 to 29, many of our Quibimers will be in Chicago demoing, sharing and showing our Radiomic solution for Hospitals and Radiology departments.

This year, QUIBIM developments are focused on the Symbiosis of Radiology and Artificial Intelligence to seamlessly integrate imaging biomarkers into radiology workflows.

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Attendees can find us at the Machine Learning Showcase – Booth #7367G  (North Building Level 3), where anyone is welcome to come over and explore the latest version of our QUIBIM Precision® Platform for medical images processing and imaging biomarkers analysis.

WANT TO DISCOVER OUR PLATFORM?

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QUIBIM will be also taking part in the Machine Learning Showcase through a communication from our CEO and Founder, Ángel Alberich-Bayarri, on November 25 at 12:30 pm. The communication is entitled “QUIBIM Precision 3.0: AI as a Means, Not an End, for Imaging Biomarkers Integration in Clinical Practice” and shares QUIBIM insights about the role of AI on imaging biomarkers integration.

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Furthermore, as members of the NVIDIA Inception Program, QUIBIM will be demoing at the NVIDIA booth #6568 on November 26 at 10:00 am. Don’t miss it!

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It is a great opportunity for QUIBIM to be engaged in such a recognised event and get in touch with professionals in the fields of radiology and medical imaging.

MEET US!

Visit of the group of Dr. Regina Beets-Tan and Dr. Erik Ranschaert to QUIBIM headquarters

The satisfaction of bringing together the best experts in the world at home

Dr. Luis Martí-Bonmatí (QUIBIM co-founder and director of advisory board) and myself had been locally organising the joint congress of the European Society of Oncological Imaging (ESOI) and the European Society of Medical Imaging Informatics (EuSoMII) for approximately 1 year, and the event finally took place past October from 6th to 8th at our home. The Venue was our hospital: La Fe Polytechnics and University Hospital, where we develop our professional activity and where QUIBIM headquarters are placed, since QUIBIM is a spin-off Company of La Fe Health Research Institute, the institutional arm of the hospital to perform research.

The topic of the congress was “Imaging Informatics in Oncology” and it was the result of joining both Societies fields like Oncology and Medical Imaging Informatics from ESOI and EUSOMII, respectively. The congress program combined workshops with plenary sessions. The workshops covered different concrete areas like Response to treatment, Tumor Boards, 3D printing, and Imaging Informatics for clinicians and computer scientists. The complete program can be found here.

I had the opportunity to present on our stepwise development of Imaging Biomarkers process and the associated bottlenecks for validation. Here you can find the slides of the presentation.

Our group had a really active participation, either from the Biomedical Imaging Research Group (GIBI230) from our Hospital and from QUIBIM.

The main scientific presentations were:

  1. ProstateChecker, a tool for the multi-variate analysis of Prostate Cancer from T2, diffusion and perfusion MR sequences, by David García-Juan, post-processing biomedical engineer at QUIBIM
  2. Cloud architecture for Imaging Biomarkers analysis, by Rafael Hernández, CTO at QUIBIM
  3. Spatial registration on PET-CT scans and quantitative structured report for treatment response evaluation on lymphoma patients, by Fabio García-Castro, post-processing biomedical engineer at QUIBIM
  4. Web application for PI-RADS 2.0 Structured Reporting, by Enrique Ruiz-Martínez, CTO at GIBI230 group
  5. Business analytic, metric, key performance indicator. Automating the monitorization of performance indicators in Radiology departments, by Enrique Ruiz-Martinez, CTO at GIBI230 group
  6. Platform for the integration of Imaging Biomarkers in Radiology Departments, by Enrique Ruiz-Martinez, CTO at GIBI230 group
  7. Integration of Redmine as a tool to manage Clinical Trials in Radiology, by Amadeo Ten-Esteve, Clinical Trial Manager at GIBI230 group.
  8. Artificial intelligence techniques applied to medical imaging. Deep learning applied to automated chest X-ray screening, by Belén Fos-Guarinos, internship biomedical engineering student at GIBI230 group.
  9. Automatic vertebrae localization in pathological spine CT using Decision Forests, by Ana Jiménez Pastor, internship telecommunications engineering student at QUIBIM.
  10. Automated segmentation of muscle using Neural Networks, by Sara Rocher, internship biomedical engineering student at GIBI230 group.
  11. Automatic classification of intensity-vs-time curves in breast DCE-MRI by K-means clustering and Dynamic Time Warping curve matching, by Fabio García-Castro, post-processing biomedical engineer at QUIBIM

In the meantime, the QUIBIM stand was boiling! With several experts interested…

QUIBIM CEO, Angel Alberich-Bayarri explaining QUIBIM advantages to interested attendees to EUSOMII - ESOI congress

QUIBIM CEO, Angel Alberich-Bayarri explaining QUIBIM advantages to interested attendees to EUSOMII – ESOI congress

Besides the opportunity to present the work of our group, we had some remarkable visits to our headquarters, like the visit of Dr. Regina Beets-Tan group together with Dr. Erik Ranschaert (see photo).

Visit of the group of Dr. Regina Beets-Tan and Dr. Erik Ranschaert to QUIBIM headquarters

Visit of the group of Dr. Regina Beets-Tan and Dr. Erik Ranschaert to QUIBIM headquarters

Industry also visited us, in this case it was Agfa Healthcare. The Global Senior Solution Manager, Mr. Chris Townend and the National Sales Manager, José Vicente Puig visited our headquarters and attended the demo of our solution.

Visit of José Vicente Puig (National Sales Manager at Agfa Healthcare) and Chris Townend (Global Senior Solution Manager at Agfa Healthcare)

Visit of José Vicente Puig (National Sales Manager at Agfa Healthcare) and Chris Townend (Global Senior Solution Manager at Agfa Healthcare)

 

The last day we were lucky to have Regina Beets-Tan and Sergey Mozorov, new presidents of ESOI and EUSOMII, respectively, at our headquarters.

 

Visit of Sergey Morozov and Regina Beets-Tan. Photo with QUIBIM founders

Visit of Sergey Morozov and Regina Beets-Tan. Photo with QUIBIM founders

 

The experience speaks by itself.