Results 201 to 210 of about 13,553 (263)

Deep Learning-Based Generation of Retinal Nerve Fibre Layer Thickness Maps from Fundus Photographs: A Comparative Analysis of U-Net Architectures for Accessible Glaucoma Assessment. [PDF]

Life (Basel)
Ohn K, Jun H, Kim YS, Whang WJ.
europepmc   +1 more source

A Lightweight and Erudite Automated BiLSTM‐Based Multi‐Cycle GAN for Retinal Blood Vessel and Optic Disc Segmentation in Fundus Images

Engineering Reports, Volume 8, Issue 8, August 2026.
This graphical abstract presents a lightweight and automated BiLSTM‐based Multi‐Cycle GAN framework for retinal blood vessel and optic disc segmentation in fundus images. Initially, fundus images undergo preprocessing, including green channel extraction, denoising, resizing, and dataset splitting.
Rasmita Kumari Mohanty, Amaravarapu Pramod Kumar, Yuvaraju Macha, Agraharam Siva Kumar, J. Srinivas, G. Shyama Chandra Prasad, Rajesh Kumar Verma, Shashi Kant   +7 more
wiley   +1 more source

A TV-BM3D Iterative Algorithm for VMAT-CT Reconstruction. [PDF]

J Imaging
Chien CL, Guo B, Zhang R.
europepmc   +1 more source

AI‐Powered Gradient Echo Plural Contrast Imaging (AI‐GEPCI)—A Comprehensive Neurological Protocol From a Single MRI Scan

Journal of Magnetic Resonance Imaging, Volume 64, Issue 2, Page 346-358, August 2026.
ABSTRACT Background MRI is essential for diagnosing and monitoring neurological diseases. Conventional protocols require multiple sequences to obtain complementary contrasts, increasing scan time, cost, and tolerability. Generating multiple contrasts from a single acquisition may streamline workflow while maintaining clinical utility.
Jeramy Lewis, Manu S. Goyal, Gregory F. Wu, Yuyang Hu, Alexander L. Sukstanskii, Satya V. V. N. Kothapalli, Anne H. Cross, Ulugbek Kamilov, Dmitriy A. Yablonskiy   +8 more
wiley   +1 more source

Multimodal medical image reconstruction and organ-wise disease classification using a hybrid deep learning-Kalman filtering framework. [PDF]

Front Med (Lausanne)
Arif S.
europepmc   +1 more source

Knowledge‐distilled diffusion models for improving cone‐beam CT image quality with meta‐learning under imbalanced data

Medical Physics, Volume 53, Issue 8, August 2026.
Abstract Background Adaptive radiation therapy (ART) relies on daily cone‐beam CT (CBCT), yet its limited image quality hinders accurate dose calculation, particularly under substantial anatomical changes. Purpose To overcome the clinical challenge of scarce paired planning CT (pCT) data versus abundant unpaired CBCTs, we propose a framework driven by ...
Joonil Hwang, Sangjoon Park, Seungryong Cho, Jin Sung Kim   +3 more
wiley   +1 more source

Quantitative and Qualitative Evaluation of a Confidence-Aware Transformer-Based Super-Resolution Framework for Panoramic Radiographs. [PDF]

Int Dent J
Lee J, An CH, An SY, Kim EK, Kwon YE.
europepmc   +1 more source

Product-of-Gaussian-mixture diffusion models for joint nonlinear MRI reconstruction. [PDF]

J Math Imaging Vis
Nagler L, Zach M, Pock T.
europepmc   +1 more source

China runoff-field forecasting based on cross-scale gating and basin-topology attention. [PDF]

PLoS One
Li A, He X, Yang K, Ge W, Hua J.
europepmc   +1 more source

Force-controlled robotic ultrasound elastography enhances diagnostic consistency for thyroid nodules. [PDF]

Insights Imaging
Yan T, Le X, Xie L, Qiu X, Cheng D, Pei C, Hu L.   +6 more
europepmc   +1 more source