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How to build the best medical image segmentation algorithm using foundation models: a comprehensive empirical study with Segment Anything Model

How to build the best medical image segmentation algorithm using foundation models: a comprehensive empirical study with Segment Anything Model

15 April 2024
Han Gu
Haoyu Dong
Jichen Yang
Maciej Mazurowski
    MedIm
    VLM
ArXivPDFHTML

Papers citing "How to build the best medical image segmentation algorithm using foundation models: a comprehensive empirical study with Segment Anything Model"

16 / 16 papers shown
Title
SurgiSAM2: Fine-tuning a foundational model for surgical video anatomy segmentation and detection
Devanish N. Kamtam
Joseph B. Shrager
Satya Deepya Malla
Xiaohan Wang
Nicole Lin
Juan J. Cardona
Serena Yeung-Levy
Clarence Hu
VLM
40
0
0
05 Mar 2025
Customize Segment Anything Model for Multi-Modal Semantic Segmentation
  with Mixture of LoRA Experts
Customize Segment Anything Model for Multi-Modal Semantic Segmentation with Mixture of LoRA Experts
Chenyang Zhu
Bin Xiao
Lin Shi
Shoukun Xu
Xu Zheng
MoE
80
6
0
05 Dec 2024
Optimized Vessel Segmentation: A Structure-Agnostic Approach with Small
  Vessel Enhancement and Morphological Correction
Optimized Vessel Segmentation: A Structure-Agnostic Approach with Small Vessel Enhancement and Morphological Correction
Dongning Song
Weijian Huang
Jiarun Liu
Md Jahidul Islam
Hao Yang
Shanshan Wang
60
0
0
22 Nov 2024
Sam2Rad: A Segmentation Model for Medical Images with Learnable Prompts
Sam2Rad: A Segmentation Model for Medical Images with Learnable Prompts
Assefa Seyoum Wahd
B. Felfeliyan
Yuyue Zhou
Shrimanti Ghosh
Adam McArthur
Jiechen Zhang
Jacob L. Jaremko
A. Hareendranathan
VLM
MedIm
22
0
0
10 Sep 2024
Segment anything model 2: an application to 2D and 3D medical images
Segment anything model 2: an application to 2D and 3D medical images
Haoyu Dong
Han Gu
Yaqian Chen
Jichen Yang
Yuwen Chen
Maciej Mazurowski
VLM
MedIm
19
6
0
01 Aug 2024
Foundation Models for Biomedical Image Segmentation: A Survey
Foundation Models for Biomedical Image Segmentation: A Survey
Ho Hin Lee
Yu Gu
Theodore Zhao
Yanbo Xu
Jianwei Yang
...
Mu-Hsin Wei
Bennett A. Landman
Yuankai Huo
Alberto Santamaría-Pang
Hoifung Poon
MedIm
VLM
25
7
0
15 Jan 2024
MA-SAM: Modality-agnostic SAM Adaptation for 3D Medical Image
  Segmentation
MA-SAM: Modality-agnostic SAM Adaptation for 3D Medical Image Segmentation
Cheng Chen
Juzheng Miao
Dufan Wu
Zhiling Yan
Sekeun Kim
...
Lichao Sun
Xiang Li
Tianming Liu
Pheng-Ann Heng
Quanzheng Li
MedIm
38
27
0
16 Sep 2023
Polyp-SAM: Transfer SAM for Polyp Segmentation
Polyp-SAM: Transfer SAM for Polyp Segmentation
Yuheng Li
Mingzhe Hu
Xiaofeng Yang
MedIm
151
74
0
29 Apr 2023
Segment Anything Model for Medical Images?
Segment Anything Model for Medical Images?
Yuhao Huang
Yitian Zhao
Lei Mou
H. Fu
Ao Chang
...
Lei Li
Vicente Grau
M. Akiba
Fajin Dong
Jiang-Dong Liu
VLM
72
276
0
28 Apr 2023
SkinSAM: Empowering Skin Cancer Segmentation with Segment Anything Model
SkinSAM: Empowering Skin Cancer Segmentation with Segment Anything Model
Mingzhe Hu
Yuheng Li
Xiaofeng Yang
VLM
131
42
0
27 Apr 2023
Customized Segment Anything Model for Medical Image Segmentation
Customized Segment Anything Model for Medical Image Segmentation
Kaiwen Zhang
Dong Liu
MedIm
VLM
92
276
0
26 Apr 2023
AdaptFormer: Adapting Vision Transformers for Scalable Visual
  Recognition
AdaptFormer: Adapting Vision Transformers for Scalable Visual Recognition
Shoufa Chen
Chongjian Ge
Zhan Tong
Jiangliu Wang
Yibing Song
Jue Wang
Ping Luo
135
631
0
26 May 2022
Robust and Efficient Medical Imaging with Self-Supervision
Robust and Efficient Medical Imaging with Self-Supervision
Shekoofeh Azizi
Laura J. Culp
Jan Freyberg
Basil Mustafa
Sebastien Baur
...
Geoffrey E. Hinton
N. Houlsby
Alan Karthikesalingam
Mohammad Norouzi
Vivek Natarajan
OOD
57
49
0
19 May 2022
UniMiSS: Universal Medical Self-Supervised Learning via Breaking
  Dimensionality Barrier
UniMiSS: Universal Medical Self-Supervised Learning via Breaking Dimensionality Barrier
Yutong Xie
Jianpeng Zhang
Yong-quan Xia
Qi Wu
MedIm
46
63
0
17 Dec 2021
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
255
5,353
0
11 Nov 2021
U-Net: Convolutional Networks for Biomedical Image Segmentation
U-Net: Convolutional Networks for Biomedical Image Segmentation
Olaf Ronneberger
Philipp Fischer
Thomas Brox
SSeg
3DV
226
9,999
0
18 May 2015
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