A deep learning framework for the detection and quantification of drusen and reticular pseudodrusen on optical coherence tomography

no code implementations • 5 Apr 2022 • Roy Schwartz, Hagar Khalid, Sandra Liakopoulos, Yanling Ouyang, Coen de Vente, Cristina González-Gonzalo, Aaron Y. Lee, Robyn Guymer, Emily Y. Chew, Catherine Egan, Zhichao Wu, Himeesh Kumar, Joseph Farrington, Clara I. Sánchez, Adnan Tufail

Methods - A DL framework was developed consisting of a classification model and an out-of-distribution (OOD) detection model for the identification of ungradable scans; a classification model to identify scans with drusen or RPD; and an image segmentation model to independently segment lesions as RPD or drusen.

Classification OOD Detection +1

Improving Automated COVID-19 Grading with Convolutional Neural Networks in Computed Tomography Scans: An Ablation Study

no code implementations • 21 Sep 2020 • Coen de Vente, Luuk H. Boulogne, Kiran Vaidhya Venkadesh, Cheryl Sital, Nikolas Lessmann, Colin Jacobs, Clara I. Sánchez, Bram van Ginneken

This paper identifies a variety of components that increase the performance of CNN-based algorithms for COVID-19 grading from CT images.

Computed Tomography (CT) Transfer Learning

A Global Benchmark of Algorithms for Segmenting Late Gadolinium-Enhanced Cardiac Magnetic Resonance Imaging

no code implementations • 26 Apr 2020 • Zhaohan Xiong, Qing Xia, Zhiqiang Hu, Ning Huang, Cheng Bian, Yefeng Zheng, Sulaiman Vesal, Nishant Ravikumar, Andreas Maier, Xin Yang, Pheng-Ann Heng, Dong Ni, Caizi Li, Qianqian Tong, Weixin Si, Elodie Puybareau, Younes Khoudli, Thierry Geraud, Chen Chen, Wenjia Bai, Daniel Rueckert, Lingchao Xu, Xiahai Zhuang, Xinzhe Luo, Shuman Jia, Maxime Sermesant, Yashu Liu, Kuanquan Wang, Davide Borra, Alessandro Masci, Cristiana Corsi, Coen de Vente, Mitko Veta, Rashed Karim, Chandrakanth Jayachandran Preetha, Sandy Engelhardt, Menyun Qiao, Yuanyuan Wang, Qian Tao, Marta Nunez-Garcia, Oscar Camara, Nicolo Savioli, Pablo Lamata, Jichao Zhao

Segmentation of cardiac images, particularly late gadolinium-enhanced magnetic resonance imaging (LGE-MRI) widely used for visualizing diseased cardiac structures, is a crucial first step for clinical diagnosis and treatment.

Left Atrium Segmentation