activity
20222024
most citedSkinSAM: Empowering Skin Cancer Segmentation with Segment Anything Model

44 citations · 88 across the 7 of their papers we have counts for

collaborators

7 papers

physics.med-ph2024

Current Progress of Digital Twin Construction Using Medical Imaging

Feng Zhao, Yizhou Wu, Mingzhe Hu +4

Medical imaging has played a pivotal role in advancing and refining digital twin technology, allowing for the development of highly personalized virtual models that represent human…

cs.CV2023

Attention-Driven Lightweight Model for Pigmented Skin Lesion Detection

Mingzhe Hu, Xiaofeng Yang

This study presents a lightweight pipeline for skin lesion detection, addressing the challenges posed by imbalanced class distribution and subtle or atypical appearances of some le…

eess.IV20238 cited

BreastSAM: A Study of Segment Anything Model for Breast Tumor Detection in Ultrasound Images

Mingzhe Hu, Yuheng Li, Xiaofeng Yang

Breast cancer is one of the most common cancers among women worldwide, with early detection significantly increasing survival rates. Ultrasound imaging is a critical diagnostic too…

eess.IV202315 cited

Polyp-SAM: Transfer SAM for Polyp Segmentation

Yuheng Li, Mingzhe Hu, Xiaofeng Yang

Colon polyps are considered important precursors for colorectal cancer. Automatic segmentation of colon polyps can significantly reduce the misdiagnosis of colon cancer and improve…

cs.CV202344 cited

SkinSAM: Empowering Skin Cancer Segmentation with Segment Anything Model

Mingzhe Hu, Yuheng Li, Xiaofeng Yang

Skin cancer is a prevalent and potentially fatal disease that requires accurate and efficient diagnosis and treatment. Although manual tracing is the current standard in clinics, a…

cs.CV202320 cited

Advancing Medical Imaging with Language Models: A Journey from N-grams to ChatGPT

Mingzhe Hu, Shaoyan Pan, Yuheng Li +1

In this paper, we aimed to provide a review and tutorial for researchers in the field of medical imaging using language models to improve their tasks at hand. We began by providing…