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One Model is All You Need: Multi-Task Learning Enables Simultaneous
  Histology Image Segmentation and Classification

One Model is All You Need: Multi-Task Learning Enables Simultaneous Histology Image Segmentation and Classification

28 February 2022
S. Graham
Q. Vu
Mostafa Jahanifar
Shan E Ahmed Raza
F. Minhas
David R. J. Snead
Nasir M. Rajpoot
    MedIm
ArXivPDFHTML

Papers citing "One Model is All You Need: Multi-Task Learning Enables Simultaneous Histology Image Segmentation and Classification"

9 / 9 papers shown
Title
A Multi-Stage Auto-Context Deep Learning Framework for Tissue and Nuclei Segmentation and Classification in H&E-Stained Histological Images of Advanced Melanoma
A Multi-Stage Auto-Context Deep Learning Framework for Tissue and Nuclei Segmentation and Classification in H&E-Stained Histological Images of Advanced Melanoma
Nima Torbati
Anastasia Meshcheryakova
Diana Mechtcheriakova
Amirreza Mahbod
44
0
0
31 Mar 2025
ModalTune: Fine-Tuning Slide-Level Foundation Models with Multi-Modal Information for Multi-task Learning in Digital Pathology
ModalTune: Fine-Tuning Slide-Level Foundation Models with Multi-Modal Information for Multi-task Learning in Digital Pathology
Vishwesh Ramanathan
Tony Xu
Pushpak Pati
Faruk Ahmed
Maged Goubran
Anne L. Martel
48
0
0
21 Mar 2025
Leveraging Weak Supervision for Cell Localization in Digital Pathology
  Using Multitask Learning and Consistency Loss
Leveraging Weak Supervision for Cell Localization in Digital Pathology Using Multitask Learning and Consistency Loss
Berke Levent Cesur
Ayse Humeyra Dur Karasayar
Pinar Bulutay
Nilgun Kapucuoglu
Cisel Aydin Mericoz
...
Javidan Osmanli
Burhan Soner Yetkili
Ibrahim Kulac
C. Koyuncu
Cigdem Demir
74
0
0
19 Dec 2024
Maximising Histopathology Segmentation using Minimal Labels via
  Self-Supervision
Maximising Histopathology Segmentation using Minimal Labels via Self-Supervision
Zeeshan Nisar
T. Lampert
68
0
0
19 Dec 2024
Tissue Concepts: supervised foundation models in computational pathology
Tissue Concepts: supervised foundation models in computational pathology
Till Nicke
Jan Raphael Schaefer
Henning Hoefener
Friedrich Feuerhake
Dorit Merhof
Fabian Kiessling
Johannes Lotz
MedIm
47
0
0
05 Sep 2024
Domain Generalization in Computational Pathology: Survey and Guidelines
Domain Generalization in Computational Pathology: Survey and Guidelines
Mostafa Jahanifar
M. Raza
Kesi Xu
T. Vuong
R. Jewsbury
...
Neda Zamanitajeddin
Jin Tae Kwak
S. Raza
F. Minhas
Nasir M. Rajpoot
OOD
28
17
0
30 Oct 2023
MoMA: Momentum Contrastive Learning with Multi-head Attention-based
  Knowledge Distillation for Histopathology Image Analysis
MoMA: Momentum Contrastive Learning with Multi-head Attention-based Knowledge Distillation for Histopathology Image Analysis
T. Vuong
J. T. Kwak
38
6
0
31 Aug 2023
Deep Learning in Breast Cancer Imaging: A Decade of Progress and Future
  Directions
Deep Learning in Breast Cancer Imaging: A Decade of Progress and Future Directions
Luyang Luo
Xi Wang
Yi-Mou Lin
Xiaoqi Ma
Andong Tan
R. Chan
V. Vardhanabhuti
W. C. Chu
Kwang-Ting Cheng
Hao Chen
33
50
0
13 Apr 2023
PanNuke Dataset Extension, Insights and Baselines
PanNuke Dataset Extension, Insights and Baselines
Jevgenij Gamper
Navid Alemi Koohbanani
Ksenija Benes
S. Graham
Mostafa Jahanifar
S. Khurram
A. Azam
K. Hewitt
Nasir M. Rajpoot
121
174
0
24 Mar 2020
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