SoftSeg: Advantages of soft versus binary training for image segmentation

18 November 2020

Papers citing "SoftSeg: Advantages of soft versus binary training for image segmentation"

6 / 6 papers shown

Title
Confidence-Based Annotation Of Brain Tumours In Ultrasound Alistair Weld L. Dixon Alfie Roddan Giulio Anichini Sophie Camp Stamatia Giannarou 52 0 0 24 Feb 2025
Noisy Image Segmentation With Soft-Dice M. Nordström Henrik Hult A. Maki F. Löfman 23 2 0 03 Apr 2023
Navigation-Oriented Scene Understanding for Robotic Autonomy: Learning to Segment Driveability in Egocentric Images Galadrielle Humblot-Renaux Letizia Marchegiani T. Moeslund Rikke Gade SSeg EgoV 20 14 0 15 Sep 2021
End-to-end Prostate Cancer Detection in bpMRI via 3D CNNs: Effects of Attention Mechanisms, Clinical Priori and Decoupled False Positive Reduction A. Saha M. Hosseinzadeh Henkjan Huisman MedIm 30 128 0 08 Jan 2021
A Survey on Deep Learning in Medical Image Analysis G. Litjens Thijs Kooi B. Bejnordi A. Setio F. Ciompi Mohsen Ghafoorian Jeroen van der Laak Bram van Ginneken C. I. Sánchez OOD 278 10,544 0 19 Feb 2017
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 247 9,042 0 06 Jun 2015