activity
20182023
most citedEstimation of Pelvic Sagittal Inclination from Anteroposterior Radiograph Using Convolutional Neural Networks: Proof-of-Concept Study

9 citations · 14 across the 8 of their papers we have counts for

collaborators

11 papers

eess.IV2023

Bone mineral density estimation from a plain X-ray image by learning decomposition into projections of bone-segmented computed tomography

Yi Gu, Yoshito Otake, Keisuke Uemura +6

Osteoporosis is a prevalent bone disease that causes fractures in fragile bones, leading to a decline in daily living activities. Dual-energy X-ray absorptiometry (DXA) and quantit…

eess.IV2023

Hybrid Representation-Enhanced Sampling for Bayesian Active Learning in Musculoskeletal Segmentation of Lower Extremities

Ganping Li, Yoshito Otake, Mazen Soufi +7

Purpose: Manual annotations for training deep learning (DL) models in auto-segmentation are time-intensive. This study introduces a hybrid representation-enhanced sampling strategy…

cs.CV2023

MSKdeX: Musculoskeletal (MSK) decomposition from an X-ray image for fine-grained estimation of lean muscle mass and muscle volume

Yi Gu, Yoshito Otake, Keisuke Uemura +7

Musculoskeletal diseases such as sarcopenia and osteoporosis are major obstacles to health during aging. Although dual-energy X-ray absorptiometry (DXA) and computed tomography (CT…

eess.IV2022

BMD-GAN: Bone mineral density estimation using x-ray image decomposition into projections of bone-segmented quantitative computed tomography using hierarchical learning

Yi Gu, Yoshito Otake, Keisuke Uemura +4

We propose a method for estimating the bone mineral density (BMD) from a plain x-ray image. Dual-energy X-ray absorptiometry (DXA) and quantitative computed tomography (QCT) provid…

cs.CV2020★ 1 cited

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…

eess.IV2019★ 9 cited

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…