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On the Out of Distribution Robustness of Foundation Models in Medical
  Image Segmentation

On the Out of Distribution Robustness of Foundation Models in Medical Image Segmentation

18 November 2023
D. M. Nguyen
Tan Ngoc Pham
Nghiem Tuong Diep
Nghi Quoc Phan
Quang Pham
Vinh Tong
Binh T. Nguyen
Ngan Hoang Le
Nhat Ho
Pengtao Xie
Daniel Sonntag
Mathias Niepert
    VLM
    UQCV
    OOD
ArXivPDFHTML

Papers citing "On the Out of Distribution Robustness of Foundation Models in Medical Image Segmentation"

8 / 8 papers shown
Title
Deep Learning for Ophthalmology: The State-of-the-Art and Future Trends
Deep Learning for Ophthalmology: The State-of-the-Art and Future Trends
Duy M. Nguyen
Hasan Md Tusfiqur Alam
Trung Quoc Nguyen
Devansh Srivastav
H. Profitlich
Ngan Le
Daniel Sonntag
59
2
0
07 Jan 2025
ASPS: Augmented Segment Anything Model for Polyp Segmentation
ASPS: Augmented Segment Anything Model for Polyp Segmentation
Huiqian Li
Dingwen Zhang
Jieru Yao
Longfei Han
Zhongyu Li
Jiawei Han
75
10
0
30 Jun 2024
HoneyBee: A Scalable Modular Framework for Creating Multimodal Oncology
  Datasets with Foundational Embedding Models
HoneyBee: A Scalable Modular Framework for Creating Multimodal Oncology Datasets with Foundational Embedding Models
Aakash Tripathi
Asim Waqas
Yasin Yilmaz
Ghulam Rasool
41
5
0
13 May 2024
Segment Anything Model for Medical Images?
Segment Anything Model for Medical Images?
Yuhao Huang
Yitian Zhao
Lei Mou
Huazhu Fu
Ao Chang
...
Lei Li
Vicente Grau
M. Akiba
Fajin Dong
Jiang-Dong Liu
VLM
80
315
0
28 Apr 2023
Masked Autoencoders Are Scalable Vision Learners
Masked Autoencoders Are Scalable Vision Learners
Kaiming He
Xinlei Chen
Saining Xie
Yanghao Li
Piotr Dollár
Ross B. Girshick
ViT
TPM
324
7,544
0
11 Nov 2021
MS-Net: Multi-Site Network for Improving Prostate Segmentation with
  Heterogeneous MRI Data
MS-Net: Multi-Site Network for Improving Prostate Segmentation with Heterogeneous MRI Data
Quande Liu
Qi Dou
Lequan Yu
Pheng Ann Heng
OOD
90
276
0
09 Feb 2020
Dropout as a Bayesian Approximation: Representing Model Uncertainty in
  Deep Learning
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Y. Gal
Zoubin Ghahramani
UQCV
BDL
299
9,202
0
06 Jun 2015
U-Net: Convolutional Networks for Biomedical Image Segmentation
U-Net: Convolutional Networks for Biomedical Image Segmentation
Olaf Ronneberger
Philipp Fischer
Thomas Brox
SSeg
3DV
451
76,262
0
18 May 2015
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