Paper Abstract and Keywords |
Presentation |
2023-03-07 16:50
[Short Paper]
Extraction of kidney and renal tumors in a multi-temporal contrast-enhanced CT image database Dai Nishioka, Kento Nishihira, Kaito Koshino, Hidenobu Suzuki, Yoshiki Kawata (Tokushima Univ.), Yuki Kobari (TWMU), Atsushi Ikeda (U. Tsukuba), Noboru Niki (Medical Science Institute Inc.) MI2022-125 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
To develop a highly accurate differentiation method for malignant and benign tumors by precisely analyzing renal and renal tumors from multi-temporal 3D contrast-enhanced CT images. For this purpose, we will construct a database of 200 cases of kidney and renal tumors in multi-temporal contrast-enhanced CT images. Using this database, five types of kidney and renal tumors ( Clear cell renal cell carcinoma, Papillary renal cell carcinoma, Achoromatic renal cell carcinoma, Angiomyolipoma, Oncocytoma) were extracted with high speed and high accuracy using 3D U-Net, and the images were clustered by gender, age, volume, shape, type, non-contrast, arterial phase, portal vein phase, and equilibrium phase images. phase, arterial phase, portal vein phase, and equilibrium phase images. The circulatory dynamics of small-diameter renal tumors are analyzed to demonstrate a highly accurate method for differentiating small-diameter renal tumors. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
Kidney and renal tumors / Multi-temporal contrast-enhanced CT image database / learning data / U-Net / / / / |
Reference Info. |
IEICE Tech. Rep., vol. 122, no. 417, MI2022-125, pp. 210-211, March 2023. |
Paper # |
MI2022-125 |
Date of Issue |
2023-02-27 (MI) |
ISSN |
Online edition: ISSN 2432-6380 |
Copyright and reproduction |
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MI2022-125 |
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