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20242026
most citedMAISI: Medical AI for Synthetic Imaging

2 citations · 3 across the 6 of their papers we have counts for

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6 papers · 1 filter

cs.CV2026

Align then Refine: Text-Guided 3D Prostate Lesion Segmentation

Cuiling Sun, Linkai Peng, Adam Murphy +9

Automated 3D segmentation of prostate lesions from biparametric MRI (bp-MRI) is essential for reliable algorithmic analysis, but achieving high precision remains challenging. Volum…

cs.CV20251 cited

MAISI-v2: Accelerated 3D High-Resolution Medical Image Synthesis with Rectified Flow and Region-specific Contrastive Loss

Can Zhao, Pengfei Guo, Dong Yang +7

Medical image synthesis is an important topic for both clinical and research applications. Recently, diffusion models have become a leading approach in this area. Despite their str…

cs.CV2025

Reasoning Visual Language Model for Chest X-Ray Analysis

Andriy Myronenko, Dong Yang, Baris Turkbey +10

Vision-language models (VLMs) have shown strong promise for medical image analysis, but most remain opaque, offering predictions without the transparent, stepwise reasoning clinici…

cs.CV2025

VILA-M3: Enhancing Vision-Language Models with Medical Expert Knowledge

Vishwesh Nath, Wenqi Li, Dong Yang +22

Generalist vision language models (VLMs) have made significant strides in computer vision, but they fall short in specialized fields like healthcare, where expert knowledge is esse…

cs.CV2024

VISTA3D: A Unified Segmentation Foundation Model For 3D Medical Imaging

Yufan He, Pengfei Guo, Yucheng Tang +11

Foundation models for interactive segmentation in 2D natural images and videos have sparked significant interest in building 3D foundation models for medical imaging. However, the…

cs.CV2024

Location-based Radiology Report-Guided Semi-supervised Learning for Prostate Cancer Detection

Alex Chen, Nathan Lay, Stephanie Harmon +6

Prostate cancer is one of the most prevalent malignancies in the world. While deep learning has potential to further improve computer-aided prostate cancer detection on MRI, its ef…