BACKGROUND: The optimal repair of ventral hernia remains unknown. We aimed to evaluate the results after robotic-assisted laparoscopic transabdominal repair with retrorectus mesh placement (rRetrorectus) compared with laparoscopic intraperitoneal onl...
PURPOSE: To validate the diagnostic performance of commercially available, deep learning-based automatic white matter hyperintensity (WMH) segmentation algorithm for classifying the grades of the Fazekas scale and differentiating subcortical vascular...
INTRODUCTION: While minimally invasive surgery (MIS) has transformed the treatment landscape of surgical care, its utilization is not well understood. The newly released Nationwide Ambulatory Surgery Sample allows for more accurate estimates of MIS v...
We aimed to compare three robot-assisted radical prostatectomy (RARP) approaches-Retzius sparing (RS), extraperitoneal (EP), and transperitoneal (TP)-performed at our institution using the da Vinci single-port (SP) platform (Intuitive Surgical, Sunn...
Journal of neuroengineering and rehabilitation
Sep 14, 2022
BACKGROUND: Robot-assisted gait training (RAGT) is a practical treatment that can complement conventional rehabilitation by providing high-intensity repetitive training for patients with stroke. RAGT systems are usually either of the end-effector or ...
Background Approximately 40% of pancreatic tumors smaller than 2 cm are missed at abdominal CT. Purpose To develop and to validate a deep learning (DL)-based tool able to detect pancreatic cancer at CT. Materials and Methods Retrospectively collected...
BACKGROUND: The purpose of this investigation was to develop a computer-assisted detection system based on a deep convolutional neural network (CNN) algorithm and to evaluate the accuracy and usefulness of this system for the detection of alveolar bo...
Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology
Sep 12, 2022
BACKGROUND: Deep learning (DL)-based attenuation correction (AC) is promising to improve myocardial perfusion (MP) SPECT. We aimed to optimize and compare the DL-based direct and indirect AC methods, with and without SPECT and CT mismatch.
PURPOSE: To develop and validate a deep learning-based reconstruction framework for highly accelerated two-dimensional (2D) phase contrast (PC-MRI) data with accurate and precise quantitative measurements.
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