9 citations · 14 across the 3 of their papers we have counts for
5 papers
Automated segmentation of an intensity calibration phantom in clinical CT images using a convolutional neural network
Keisuke Uemura, Yoshito Otake, Masaki Takao +4
Purpose: To apply a convolutional neural network (CNN) to develop a system that segments intensity calibration phantom regions in computed tomography (CT) images, and to test the s…
Estimation of Pelvic Sagittal Inclination from Anteroposterior Radiograph Using Convolutional Neural Networks: Proof-of-Concept Study
Ata Jodeiri, Yoshito Otake, Reza A. Zoroofi +5
Alignment of the bones in standing position provides useful information in surgical planning. In total hip arthroplasty (THA), pelvic sagittal inclination (PSI) angle in the standi…
Region-based Convolution Neural Network Approach for Accurate Segmentation of Pelvic Radiograph
Ata Jodeiri, Reza A. Zoroofi, Yuta Hiasa +4
With the increasing usage of radiograph images as a most common medical imaging system for diagnosis, treatment planning, and clinical studies, it is increasingly becoming a vital…
Automated Muscle Segmentation from Clinical CT using Bayesian U-Net for Personalized Musculoskeletal Modeling
Yuta Hiasa, Yoshito Otake, Masaki Takao +3
We propose a method for automatic segmentation of individual muscles from a clinical CT. The method uses Bayesian convolutional neural networks with the U-Net architecture, using M…
Cross-modality image synthesis from unpaired data using CycleGAN: Effects of gradient consistency loss and training data size
Yuta Hiasa, Yoshito Otake, Masaki Takao +5
CT is commonly used in orthopedic procedures. MRI is used along with CT to identify muscle structures and diagnose osteonecrosis due to its superior soft tissue contrast. However,…