Prospects of structural similarity index for medical image analysis

V Mudeng, M Kim, S Choe - Applied Sciences, 2022 - mdpi.com
An image quality matrix provides a significant principle for objectively observing an image
based on an alteration between the original and distorted images. During the past two …

A review of advances in image-guided orthopedic surgery

X Fan, Q Zhu, P Tu, L Joskowicz… - Physics in Medicine & …, 2023 - iopscience.iop.org
Orthopedic surgery remains technically demanding due to the complex anatomical
structures and cumbersome surgical procedures. The introduction of image-guided …

Evaluation of DIR algorithm performance in real patients for radiotherapy treatments: A systematic review of operator-dependent strategies

C Dossun, C Niederst, G Noel, P Meyer - Physica Medica, 2022 - Elsevier
Purpose The performance of deformable medical image registration (DIR) algorithms has
become a major concern. Methods We aimed to obtain updated information on DIR …

An automated unsupervised deep learning–based approach for diabetic retinopathy detection

H Naz, R Nijhawan, NJ Ahuja - Medical & Biological Engineering & …, 2022 - Springer
Abstract As per the International Diabetes Federation (IDF) report, 35–60% of people
suffering from diabetic retinopathy (DR) have a history of diabetes. DR is one of the primary …

Contour‐guided deep learning based deformable image registration for dose monitoring during CBCT‐guided radiotherapy of prostate cancer

C Hemon, B Rigaud, A Barateau… - Journal of applied …, 2023 - Wiley Online Library
Purpose To evaluate deep learning (DL)‐based deformable image registration (DIR) for
dose accumulation during radiotherapy of prostate cancer patients. Methods and Materials …

Empirical evidence of the task-adapted reconstruction framework for joint CT reconstruction and segmentation

E Valat, A Biguri, LE Sanchez, C McCague… - Applied Mathematics …, 2024 - aimsciences.org
Powered by machine learning, computer-aided diagnostics support clinicians by
streamlining their work. In cancer screening, for instance, this technique often involves an …

Distillation Learning Guided by Image Reconstruction for One-Shot Medical Image Segmentation

F Zhou, Y Zhou, L Wang, Y Peng, DE Carlson… - arxiv preprint arxiv …, 2024 - arxiv.org
Traditional one-shot medical image segmentation (MIS) methods use registration networks
to propagate labels from a reference atlas or rely on comprehensive sampling strategies to …

Unsupervised deep learning-based medical image registration: a survey

T Duan, W Chen, M Ruan, X Zhang… - Physics in Medicine & …, 2025 - iopscience.iop.org
In recent decades, medical image registration technology has undergone significant
development, becoming one of the core technologies in medical image analysis. With the …

[HTML][HTML] Longitudinal Image Data for Outcome Modeling

JE van Timmeren, J Bussink, P Koopmans, RJ Smeenk… - Clinical Oncology, 2024 - Elsevier
In oncology, medical imaging is crucial for diagnosis, treatment planning and therapy
execution. Treatment responses can be complex and varied and are known to involve …

Development of a Subtraction Processing Technology for Assistance in the Comparative Interpretation of Mammograms

C Kai, S Kondo, T Otsuka, A Yoshida, I Sato… - Diagnostics, 2024 - mdpi.com
A comparative interpretation of mammograms has become increasingly important, and it is
crucial to develop subtraction processing and registration methods for mammograms …