3 citations · 3 across the 3 of their papers we have counts for
4 papers
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…
RadiomicsFill-Mammo: Synthetic Mammogram Mass Manipulation with Radiomics Features
Inye Na, Jonghun Kim, Eun Sook Ko +1
Motivated by the question, "Can we generate tumors with desired attributes?'' this study leverages radiomics features to explore the feasibility of generating synthetic tumor image…
Synthetic Tumor Manipulation: With Radiomics Features
Inye Na, Jonghun Kim, Hyunjin Park
We introduce RadiomicsFill, a synthetic tumor generator conditioned on radiomics features, enabling detailed control and individual manipulation of tumor subregions. This condition…