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The Dice loss in the context of missing or empty labels: Introducing
  $Φ$ and $ε$

The Dice loss in the context of missing or empty labels: Introducing ΦΦΦ and εεε

19 July 2022
Sofie Tilborghs
J. Bertels
D. Robben
Dirk Vandermeulen
F. Maes
ArXivPDFHTML

Papers citing "The Dice loss in the context of missing or empty labels: Introducing $Φ$ and $ε$"

4 / 4 papers shown
Title
A label-free and data-free training strategy for vasculature
  segmentation in serial sectioning OCT data
A label-free and data-free training strategy for vasculature segmentation in serial sectioning OCT data
Etienne Chollet
Yael Balbastre
C. Magnain
Bruce Fischl
Hui Wang
20
1
0
22 May 2024
Dice Semimetric Losses: Optimizing the Dice Score with Soft Labels
Dice Semimetric Losses: Optimizing the Dice Score with Soft Labels
Zifu Wang
Teodora Popordanoska
J. Bertels
Robin Lemmens
Matthew B. Blaschko
24
10
0
28 Mar 2023
HALOS: Hallucination-free Organ Segmentation after Organ Resection
  Surgery
HALOS: Hallucination-free Organ Segmentation after Organ Resection Surgery
Anne-Marie Rickmann
Murong Xu
Tom Nuno Wolf
Oksana P. Kovalenko
Christian Wachinger
SSeg
17
3
0
14 Mar 2023
Unified Focal loss: Generalising Dice and cross entropy-based losses to
  handle class imbalanced medical image segmentation
Unified Focal loss: Generalising Dice and cross entropy-based losses to handle class imbalanced medical image segmentation
Michael Yeung
Evis Sala
Carola-Bibiane Schönlieb
L. Rundo
30
393
0
08 Feb 2021
1