Documents et medias

Publications scientifiques

Publications scientifiques

Imaging biomarker phenotyping system (iBiopsy) to accelerate hepatocellular carcinoma (HCC) drug development

Yan Liu [1], Corinne Ramos [1], Pierre Baudot [1], Johan Brag [1], Olivier Lucidarme [2] - Affiliations: [1] Median Technologies, Valbonne, France. [2] Radiology Unit, Pitié Salpétrière Hospital, APHP, Paris, France

Current drug therapies in HCC remain limited because of substantial genomic, cellular and molecular heterogeneity of the liver tumor microenvironment (TME). This heterogeneity has implications for tumor development, immune response and cellular invasion and is compounded by multiple molecular pathways related to the various HCC etiologies. In this context, it is challenging to find biomarkers that are predictive of therapeutic response or outcome. A systems biology approach leveraging the iBiopsy phenotyping platform to automatically detect HCC and TME subtypes using non-invasive medical imaging could help identify specific disease pathways and accelerate HCC drug development.

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DUALTAIL-NET for Liver Segmentation on Abdominal CT Images

Vladimir Groza [1], Johan Brag [1], Michael Auffret [1] - Affiliations: [1]: Median Technologies, Valbonne, France

Poster presented at The IEEE International Symposium on Biomedical Imaging (ISBI) 2019 | Venice, Italy | April 8-11, 2019
In clinical trials, the evaluation of CT/MRI images is usually done manually or with the use of semi-automatic segmentation techniques. Liver segmentation, as well as segmentations of other organs such as prostate, lung, is a crucial step in computer-aided systems for cancer detection. In order to improve the quality and performance of diagnosis computer-aided systems became popular, where deep learning approach demonstrates its potential and strengths as robust and powerful tool in particular for medical image segmentation. This work presents a novel deep convolutional neural network architecture DualTail-Net in application for automatic liver segmentation on abdominal CT images.

Can we improve cost effectiveness of oncology clinical trials workflow? A prospective RECIST 1.1 study

Hubert Beaumont [1], Antoine Iannessi [2], Catherine Klifa [1], Sebastien Patriti [2] - Affiliations: [1] Median Technologies, Valbonne, France, [2] Centre Antoine Lacassagne, Nice, France

Poster présenté au congrès ESMO ASIA 2018, 23-25 Novembre, Singapore

Assessing the Relevance of Multi-planar MRI Acquisitions for Prostate Segmentation Using Deep Learning Techniques

Rocío Cabrera Lozoya, PhD [1], Antoine Iannessi, MD [2], Johan Brag, MSc [1], Sebastien Patriti [2], Estanislao Oubel, PhD [1] - Affiliations: [1] Median Technologies, France, [2] Centre Antoine Lacassagne, France

Poster présenté pendant la conférence SPIE Imaging, Fevrier 2018, San Diego, USA

Reproducibility of mRECIST criteria for assessment of HCC treated by anti-VEGFR therapy: Impact of the reader's experience

Hubert Beaumont [1], Sophie Egels [2], Nathalie Faye [1], Catherine Klifa [1], Antoine Iannessi [3], Eric Bonnard [3], Olivier Lucidarme [2] -Affiliations: [1] Median Technologies, Valbonne, France ; [2] Hôpital La Pitié Salpétrière, Paris, France; [3] Centre Antoine Lacassagne, Nice, France

Poster présenté à l’occasion du Congrès ESMO 2018, Munich. L’étude a été réalisée en collaboration avec l’Hopital La Pitié-Salpêtriere (AP-HP, France) et le centre anticancer Antoine Lacassagne (Nice, France).

Documents et medias

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