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Yong Yu

Researcher at University of Rochester

Publications -  27
Citations -  284

Yong Yu is an academic researcher from University of Rochester. The author has contributed to research in topics: Flat panel detector & Breast imaging. The author has an hindex of 8, co-authored 22 publications receiving 253 citations.

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Patent

The methods and apparatus of cone beam ct imaging and image-guided procedures

TL;DR: In this paper, the authors present a system for detecting and biopsying lesions with a cone beam computed tomography (CBCT) system. But the system comprises, in some embodiments, a CBCT device configured to output a conebeam CT image of at least a portion of a patient's breast and a multi-axis transport module, having at least three degrees of freedom and configured to position a biopsy needle within a 3D frame of reference based on inputs received from the cone beam CT device.
Proceedings ArticleDOI

Evaluation of flat panel detector cone beam CT breast imaging with different sizes of breast phantoms

TL;DR: The results demonstrate that the CBCTBI can detect a few millimeter-size simulated carcinoma and ~ 0.2 mm calcification with clinically acceptable mean glandular doses for different size breasts.
Proceedings ArticleDOI

A novel cone beam breast CT scanner: system evaluation

TL;DR: The results indicate that the CBBCT imaging system has much better detectability of small breast tumors compared to the conventional mammography system and all phantom masses and calcifications as well as human subjects' masses, calcifications and abnormalities can be detected faithfully using theCBBCT technique.
Proceedings ArticleDOI

Preliminary System Characterization of Flat Panel Detector-based Cone Beam CT for Breast Imaging

TL;DR: The results indicate that the FPD-CBCTBI technique effectively removes structure overlap and significantly improves the detectability of small breast tumors, and demonstrates CBCTBI offers good image quality with the radiation dose level less than or equal to that of conventional mammography.
Journal ArticleDOI

Performance of CT radiomics in predicting the overall survival of patients with stage III clear cell renal carcinoma after radical nephrectomy

TL;DR: The two prediction models showed high performance in the evaluation of OS of stage III ccRCC patients after radical nephrectomy, among which Model 2 based on ISUP grade and RS was more concise and efficient.