Optimal management strategy for salt adsorption capacity in machine learning-based flow-electrode capacitive deionization process

SI Yu, J Jeon, YU Shin, H Bae - ACS ES&T Engineering, 2024 - ACS Publications
Flow-electrode capacitive deionization (FCDI) has created a breakthrough toward a more
stable desalination performance by adopting a flow-electrode compared to existing …

Automation of membrane capacitive deionization process using reinforcement learning

N Yoon, S Park, M Son, KH Cho - Water Research, 2022 - Elsevier
Capacitive deionization (CDI) is an alternative desalination technology that uses
electrochemical ion separation. Although several attempts have been made to maximize the …

[HTML][HTML] UniverDetect: Universal landmark detection method for multidomain X-ray images

C Lu, G Yang, X Qiao, W Chen, Q Zeng - Neurocomputing, 2024 - Elsevier
Landmark detection using X-ray imaging is vital for disease screening, treatment, and
prognosis. It provides a framework for subsequent tasks, including segmentation …

[HTML][HTML] Deep reinforcement learning and convolutional autoencoders for anomaly detection of congenital inner ear malformations in clinical CT images

PL Diez, JV Sundgaard, J Margeta, K Diab… - … Medical Imaging and …, 2024 - Elsevier
Detection of abnormalities within the inner ear is a challenging task even for experienced
clinicians. In this study, we propose an automated method for automatic abnormality …

Deep learning-based workflow for hip joint morphometric parameter measurement from CT images

H Zhai, J Huang, L Li, H Tao, J Wang, K Li… - Physics in Medicine …, 2023 - iopscience.iop.org
Objective. Precise hip joint morphometry measurement from CT images is crucial for
successful preoperative arthroplasty planning and biomechanical simulations. Although …

Super-resolution landmark detection networks for medical images

R Zhang, H Mo, W Hu, B Jie, L Xu, Y He, J Ke… - Computers in Biology …, 2024 - Elsevier
Craniomaxillofacial (CMF) and nasal landmark detection are fundamental components in
computer-assisted surgery. Medical landmark detection method includes regression-based …

A deep learning-based multi-view approach to automatic 3D landmarking and deformity assessment of lower limb

R Rostamian, M Shariat Panahi, M Karimpour… - Scientific Reports, 2025 - nature.com
Anatomical Landmark detection in CT-Scan images is widely used in the identification of
skeletal disorders. However, the traditional process of manually detecting anatomical …

Reinforcement learning‐based anatomical maps for pancreas subregion and duct segmentation

S Amiri, T Vrtovec, T Mustafaev, CL Deufel… - Medical …, 2024 - Wiley Online Library
Background The pancreas is a complex abdominal organ with many anatomical variations,
and therefore automated pancreas segmentation from medical images is a challenging …

Fragment Distance-Guided Dual-Stream Learning for Automatic Pelvic Fracture Segmentation

B Zeng, H Wang, L Joskowicz, X Chen - Computerized Medical Imaging …, 2024 - Elsevier
Pelvic fracture is a complex and severe injury. Accurate diagnosis and treatment planning
require the segmentation of the pelvic structure and the fractured fragments from …

Deep reinforcement learning in medical imaging

SK Zhou, Q Wang - Deep Learning for Medical Image Analysis, 2024 - Elsevier
Deep reinforcement learning (DRL) augments the reinforcement learning framework, which
learns a sequence of actions that maximizes the expected reward, with the representative …