We developed a machine learning model for predicting prostate cancer (PCa) grades using radiomic features of magnetic resonance imaging. 112 patients diagnosed with PCa based on prostate biopsy between January 2014 and December 2021 were evaluated. L...
Novel deep learning image reconstruction (DLIR) reportedly changes the image quality characteristics based on object contrast and image noise. In clinical practice, computed tomography image noise is usually controlled by tube current modulation (TCM...
We developed an artificial intelligence (AI) technique to identify epileptic discharges (spikes) in pediatric scalp electroencephalograms (EEGs). We built a convolutional neural network (CNN) model to automatically classify steep potential images int...
We developed an artificial intelligence (AI) method for estimating fetal weights of Japanese fetuses based on the gestational weeks and the bi-parietal diameter, abdominal circumference, and femur length. The AI comprised of neural network architectu...
Since 2012, we have been developing a remote-controlled robotic system (Zerobot®) for needle insertion during computed tomography (CT)-guided interventional procedures, such as ablation, biopsy, and drainage. The system was designed via a collaborati...
A 38-year-old woman with a 2.7-cm left ureteral stenosis requiring chronic ureteral stent exchange elected to undergo robotic renal autotransplantation. Left ureteropelvic junction obstruction (UPJO) was also suspected. Robotic donor nephrectomy cont...