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Biomedical Segmentation

Collaboration with Silvana Castillo and Luis Carlos Rivera
Collaboration with Amazon Web Services


Biomedical images are useful for diagnosis, treatment, and follow-up of patients with diverse pathologies and conditions. AI-based methods are tools to analyze these images. However, this task requires the intervention of specialized medical personal, and the interpretation of the images is dependent on the perception and expertise of the specialist analyzing each image. Medical image analysis requires considerable processing times and significant use of computational resources. Due to the complexity of the data, the anatomical variations, different modalities, three-dimensionality, among other challenges of this data.

We focus on the segmentation task, i.e., to find and differentiate a structure of interest within an image. This structure could be an organ or a pathology and could be in multiple locations and have different morphologies and sizes. Thus, we are developing a general segmentation method that has an excellent performance in various tasks and is independent of the possible variations and modalities found in data. We are implementing our methodology using the data provided by the Medical Segmentation Decathlon. That is a challenge with ten different categories for different organs and pathologies.

Presentation video



Publications


QU-BraTS: MICCAI BraTS 2020 Challenge on Quantifying Uncertainty in Brain Tumor Segmentation–Analysis of Ranking Metrics and Benchmarking Results

Raghav Mehta, Angelos Filos, Ujjwal Baid, Chiharu Sako, Richard McKinley, Michael Rebsamen, Katrin Dätwyler, Raphael Meier, Piotr Radojewski, Gowtham Krishnan Murugesan, Sahil Nalawade, Chandan Ganesh, Ben Wagner, Fang F Yu, Baowei Fei, Ananth J Madhuranthakam, Joseph A Maldjian, Laura Daza, Catalina Gómez, Pablo Arbeláez, Chengliang Dai, Shuo Wang, Hadrien Raynaud, Yuanhan Mo, Elsa Angelini, Yike Guo, Wenjia Bai, Subhashis Banerjee, Linmin Pei, Murat AK, Sarahi Rosas-González, Illyess Zemmoura, Clovis Tauber, Minh H Vu, Tufve Nyholm, Tommy Löfstedt, Laura Mora Ballestar, Veronica Vilaplana, Hugh McHugh, Gonzalo Maso Talou, Alan Wang, Jay Patel, Ken Chang, Katharina Hoebel, Mishka Gidwani, Nishanth Arun, Sharut Gupta, Mehak Aggarwal, Praveer Singh, Elizabeth R Gerstner, Jayashree Kalpathy-Cramer, Nicolas Boutry, Alexis Huard, Lasitha Vidyaratne, Md Monibor Rahman, Khan M Iftekharuddin, Joseph Chazalon, Elodie Puybareau, Guillaume Tochon, Jun Ma, Mariano Cabezas, Xavier Llado, Arnau Oliver, Liliana Valencia, Sergi Valverde, Mehdi Amian, Mohammadreza Soltaninejad, Andriy Myronenko, Ali Hatamizadeh, Xue Feng, Quan Dou, Nicholas Tustison, Craig Meyer, Nisarg A Shah, Sanjay Talbar, Marc-Andr Weber, Abhishek Mahajan, Andras Jakab, Roland Wiest, Hassan M Fathallah-Shaykh, Arash Nazeri, Mikhail Milchenko, Daniel Marcus, Aikaterini Kotrotsou, Rivka Colen, John Freymann, Justin Kirby, Christos Davatzikos, Bjoern Menze, Spyridon Bakas, Yarin Gal, Tal Arbel

arXiv