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Scientific publications

Scientific publications

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 presented at ESMO ASIA 2018, Singapore, Nov. 23 -25, 2018

Feasibility of Using Deep Learning Techniques to Assess Hepatic Fibrosis Directly from Magnetic Resonance Elastography Source Images

Marc-Michel Rohé [1], Estanislao Oubel [1], Marie-Lise Grisoni [1], Stephen Djedjos [2], Robert P. Myers [2], Hohit Loomba [3] and Michael S. Middleton [3] - [1] Median Technologies - [2] Gilead - [3] UCSD

Scientific poster presented at The Liver Meeting® 2018 | AASLD – San Francisco (Nov. 9 – Nov. 13, 2018). Study was performed in collaboration with Gilead and the University of California San Diego (UCSD)

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 presented at the ESMO 2018 Congress, in Munich. Study was performed in collaboration with the French Hospital La Pitie-Salpetriere (AP-HP, France) and the Antoine Lacassagne Cancer Center (Nice, France).

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 presented at the SPIE Conference  February 2018, San Diego, USA

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