PathoSCOPE: Few-Shot Pathology Detection via Self-Supervised Contrastive Learning and Pathology-Informed Synthetic Embeddings

23 May 2025

Papers citing "PathoSCOPE: Few-Shot Pathology Detection via Self-Supervised Contrastive Learning and Pathology-Informed Synthetic Embeddings"

7 / 7 papers shown

Title
Unsupervised Pathology Detection: A Deep Dive Into the State of the Art I. Lagogiannis Felix Meissen Georgios Kaissis Daniel Rueckert OOD 103 19 0 01 Mar 2023
CFLOW-AD: Real-Time Unsupervised Anomaly Detection with Localization via Conditional Normalizing Flows Denis A. Gudovskiy Shun Ishizaka Kazuki Kozuka 72 400 0 27 Jul 2021
Mean-Shifted Contrastive Loss for Anomaly Detection Tal Reiss Yedid Hoshen 30 117 0 07 Jun 2021
PaDiM: a Patch Distribution Modeling Framework for Anomaly Detection and Localization Thomas Defard Aleksandr Setkov Angélique Loesch Romaric Audigier UQCV 59 827 0 17 Nov 2020
MADGAN: unsupervised Medical Anomaly Detection GAN using multiple adjacent brain MRI slice reconstruction Changhee Han L. Rundo K. Murao T. Noguchi Yuki Shimahara Z. '. Milacski S. Koshino Evis Sala Hideki Nakayama Shinichi Satoh MedIm 105 164 0 24 Jul 2020
Towards Visually Explaining Variational Autoencoders Wenqian Liu Runze Li Meng Zheng Srikrishna Karanam Ziyan Wu B. Bhanu Richard J. Radke Mario Sznaier 84 217 0 18 Nov 2019
Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge Spyridon Bakas M. Reyes Andras Jakab Stefan Bauer Markus Rempfler ... Jayashree Kalpathy-Cramer Keyvan Farahani Christos Davatzikos Koen van Leemput Bjoern Menze 109 1,623 0 05 Nov 2018