ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2310.00504
  4. Cited By
Exploring SAM Ablations for Enhancing Medical Segmentation in Radiology
  and Pathology

Exploring SAM Ablations for Enhancing Medical Segmentation in Radiology and Pathology

30 September 2023
Amin Ranem
Niklas Babendererde
Moritz Fuchs
Anirban Mukhopadhyay
ArXivPDFHTML

Papers citing "Exploring SAM Ablations for Enhancing Medical Segmentation in Radiology and Pathology"

3 / 3 papers shown
Title
A Systematic Review of Deep Learning-based Research on Radiology Report
  Generation
A Systematic Review of Deep Learning-based Research on Radiology Report Generation
Chang Liu
Yuanhe Tian
Yan Song
MedIm
25
15
0
23 Nov 2023
Zero-shot performance of the Segment Anything Model (SAM) in 2D medical
  imaging: A comprehensive evaluation and practical guidelines
Zero-shot performance of the Segment Anything Model (SAM) in 2D medical imaging: A comprehensive evaluation and practical guidelines
C. M. Oliveira
L. V. Moura
R. Ravazio
L. S. Kupssinskü
Otávio Parraga
Marcelo Mussi Delucis
Rodrigo C. Barros
VLM
MedIm
70
25
0
28 Apr 2023
Customized Segment Anything Model for Medical Image Segmentation
Customized Segment Anything Model for Medical Image Segmentation
Kaiwen Zhang
Dong Liu
MedIm
VLM
95
286
0
26 Apr 2023
1