Synthetic Tumor Manipulation: With Radiomics Features

Autor:	Na, Inye, Kim, Jonghun, Park, Hyunjin
Rok vydání:	2023
Předmět:	Electrical Engineering and Systems Science - Image and Video Processing Computer Science - Computer Vision and Pattern Recognition Quantitative Biology - Quantitative Methods
Druh dokumentu:	Working Paper
Popis:	We introduce RadiomicsFill, a synthetic tumor generator conditioned on radiomics features, enabling detailed control and individual manipulation of tumor subregions. This conditioning leverages conventional high-dimensional features of the tumor (i.e., radiomics features) and thus is biologically well-grounded. Our model combines generative adversarial networks, radiomics-feature conditioning, and multi-task learning. Through experiments with glioma patients, RadiomicsFill demonstrated its capability to generate diverse, realistic tumors and its fine-tuning ability for specific radiomics features like 'Pixel Surface' and 'Shape Sphericity'. The ability of RadiomicsFill to generate an unlimited number of realistic synthetic tumors offers notable prospects for both advancing medical imaging research and potential clinical applications. Comment: Paper accepted at NeurIPS 2023 Workshop: Medical Imaging meets NeurIPS
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2311.02586 Zobrazit plný text záznamu View this record from Arxiv