86 citations · 95 across the 10 of their papers we have counts for
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Mixture of Multi-Sequence Feature Difference for Contrast-Enhanced MRI Synthesis
Jonghun Kim, Junmo Kwon, Hyunjin Park
Contrast-enhanced magnetic resonance imaging (CE-MRI) is crucial for accurately diagnosing and segmenting brain tumors. However, the acquisition of CE-MRI requires injecting contra…
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…