What is Wrong with Continual Learning in Medical Image Segmentation?

What is Wrong with Continual Learning in Medical Image Segmentation?

21 October 2020

Camila González

Anirban Mukhopadhyay

Papers citing "What is Wrong with Continual Learning in Medical Image Segmentation?"

9 / 9 papers shown

Title
Memory-Efficient Prompt Tuning for Incremental Histopathology Classification Yu Zhu Kang Li Lequan Yu Pheng-Ann Heng VLM 29 0 0 22 Jan 2024
TADIL: Task-Agnostic Domain-Incremental Learning through Task-ID Inference using Transformer Nearest-Centroid Embeddings Gusseppe Bravo Rocca Peini Liu Jordi Guitart Ajay Dholakia David Ellison 19 1 0 21 Jun 2023
Generative appearance replay for continual unsupervised domain adaptation Boqi Chen Kevin Thandiackal Pushpak Pati O. Goksel CLL MedIm 27 11 0 03 Jan 2023
Domain-incremental Cardiac Image Segmentation with Style-oriented Replay and Domain-sensitive Feature Whitening Kang Li Lequan Yu Pheng-Ann Heng CLL 22 22 0 09 Nov 2022
LifeLonger: A Benchmark for Continual Disease Classification Mohammad Mahdi Derakhshani Ivona Najdenkoska Tom van Sonsbeek Xiantong Zhen Dwarikanath Mahapatra M. Worring Cees G. M. Snoek 24 31 0 12 Apr 2022
Bristle: Decentralized Federated Learning in Byzantine, Non-i.i.d. Environments Joost Verbraeken M. Vos J. Pouwelse 19 4 0 21 Oct 2021
Continual Active Learning for Efficient Adaptation of Machine Learning Models to Changing Image Acquisition Matthias Perkonigg J. Hofmanninger Georg Langs MedIm OOD 17 16 0 07 Jun 2021
Adversarial Continual Learning Sayna Ebrahimi Franziska Meier Roberto Calandra Trevor Darrell Marcus Rohrbach CLL VLM 152 197 0 21 Mar 2020
TorchIO: A Python library for efficient loading, preprocessing, augmentation and patch-based sampling of medical images in deep learning Fernando Pérez-García Rachel Sparks Sébastien Ourselin MedIm LM&MA 135 426 0 09 Mar 2020