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. 2306.12510
  4. Cited By
Comparative Analysis of Segment Anything Model and U-Net for Breast
  Tumor Detection in Ultrasound and Mammography Images

Comparative Analysis of Segment Anything Model and U-Net for Breast Tumor Detection in Ultrasound and Mammography Images

21 June 2023
Mohsen Ahmadi
Masoumeh Farhadi Nia
Sara Asgarian
Kasra Danesh
Elyas Irankhah
Ahmad Gholizadeh Lonbar
Abbas Sharifi
ArXivPDFHTML

Papers citing "Comparative Analysis of Segment Anything Model and U-Net for Breast Tumor Detection in Ultrasound and Mammography Images"

1 / 1 papers shown
Title
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
25
393
0
08 Feb 2021
1