From the 1 of 8 linked papers with an AI index.
8 papers
Multi-LLM Collaborative MRI Report Generation for Visual Instruction Tuning in Brain Oncology
Sinyoung Ra, Jonghun Kim, Hyunjin Park
The paper presents a method for building a 3D MRI‑text dataset for brain tumors and uses multiple large language models working together to generate and verify radiology reports, t…
Visual Instruction-Finetuned Language Model for Versatile Brain MR Image Tasks
Jonghun Kim, Sinyoung Ra, Hyunjin Park
LLMs have demonstrated remarkable capabilities in linguistic reasoning and are increasingly adept at vision-language tasks. The integration of image tokens into transformers has en…
Simulating Post-Neoadjuvant Chemotherapy Breast Cancer MRI via Diffusion Model with Prompt Tuning
Jonghun Kim, Hyunjin Park
Neoadjuvant chemotherapy (NAC) is a common therapy option before the main surgery for breast cancer. Response to NAC is monitored using follow-up dynamic contrast-enhanced magnetic…
Tumor Synthesis conditioned on Radiomics
Jonghun Kim, Inye Na, Eun Sook Ko +1
Due to privacy concerns, obtaining large datasets is challenging in medical image analysis, especially with 3D modalities like Computed Tomography (CT) and Magnetic Resonance Imagi…
RadiomicsRetrieval: A Customizable Framework for Medical Image Retrieval Using Radiomics Features
Inye Na, Nejung Rue, Jiwon Chung +1
Medical image retrieval is a valuable field for supporting clinical decision-making, yet current methods primarily support 2D images and require fully annotated queries, limiting c…
Privacy-Preserving Chest X-ray Classification in Latent Space with Homomorphically Encrypted Neural Inference
Jonghun Kim, Gyeongdeok Jo, Sinyoung Ra +1
Medical imaging data contain sensitive patient information requiring strong privacy protection. Many analytical setups require data to be sent to a server for inference purposes. H…