The management of a ureteral orifice injury occurring during robotic radical prostatectomy (RARP) represents a challenge for urologists. Several techniques have been proposed to treat an intraoperative injury, but intraoperative positioning of a DJ s...
PURPOSE: Various dose calculation algorithms are available for radiation therapy for cancer patients. However, these algorithms are faced with the tradeoff between efficiency and accuracy. The fast algorithms are generally less accurate, while the ac...
Development of label-free methods for accurate classification of cells with high throughput can yield powerful tools for biological research and clinical applications. We have developed a deep neural network of DINet for extracting features from cros...
IEEE journal of biomedical and health informatics
Dec 16, 2019
Segmentation of prostate in medical imaging data (e.g., CT, MRI, TRUS) is often considered as a critical yet challenging task for radiotherapy treatment. It is relatively easier to segment prostate from MR images than from CT images, due to better so...
PURPOSE: We compared cancer detection rates in patients who underwent magnetic resonance imaging cognitive guided micro-ultrasound biopsy vs robotic ultrasound magnetic resonance imaging fusion biopsy for prostate cancer.
PURPOSE: Accurate segmentation of the prostate on computed tomography (CT) for treatment planning is challenging due to CT's poor soft tissue contrast. Magnetic resonance imaging (MRI) has been used to aid prostate delineation, but its final accuracy...
BACKGROUND: The pathologic diagnosis and Gleason grading of prostate cancer are time-consuming, error-prone, and subject to interobserver variability. Machine learning offers opportunities to improve the diagnosis, risk stratification, and prognostic...
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