Results 91 to 100 of about 294 (197)

Punctured Parallel and Serial Concatenated Convolutional Codes for BPSK/QPSK Channels

, 1999
O.F. Acikel
openalex   +1 more source

Dual energy CT and deep learning for an automated volumetric segmentation of the major intracranial tissues: Feasibility and initial findings

Medical Physics, Volume 53, Issue 1, January 2026.
Abstract Background Magnetic resonance imaging (MRI) has traditionally been preferred over computed tomography (CT) for segmentation of intracranial structures due to its superior low contrast resolution. However, a reliable CT‐based segmentation could improve patient management when MRI is not practical.
Veronica Fransson, Filip Winzell, Birgitta Ramgren, Søren Christensen, Kristina Ydström, Ida Arvidsson, Niels Christian Overgaard, Kalle Åström, Anders Heyden, Johan Wassélius   +9 more
wiley   +1 more source

Performance of Serial Concatenated Convolutional Code with Dithered Golden Section Channel Interleaver over Frequency Selective Rayleigh Fading Channel

, 2005
Raghad Z. Al-Macdici
openalex   +1 more source

Convolutional recurrent U‐net for cardiac cine MRI reconstruction via effective spatio‐temporal feature exploitation

Medical Physics, Volume 53, Issue 1, January 2026.
Abstract Background Cardiac Cine Magnetic Resonance Imaging (MRI) provides dynamic visualization of the heart's structure and function but is hindered by slow acquisition, requiring repeated breath‐holds that challenge sick patients. Accelerated imaging can mitigate these issues but potentially reduce spatial and temporal resolution.
Donghang Lyu, Marius Staring, Matthias J. P. van Osch, Mariya Doneva, Hildo J. Lamb, Nicola Pezzotti   +5 more
wiley   +1 more source

A deep‐learning model for one‐shot transcranial ultrasound simulation and phase aberration correction

Medical Physics, Volume 53, Issue 1, January 2026.
Abstract Background Transcranial ultrasound is a promising non‐invasive neuromodulation technique with applications, including neuronal activity modulation, blood–brain barrier opening, targeted drug delivery, and thermal ablation. Its ability to deliver focused ultrasound waves to precise brain regions has led to over 50 clinical trials targeting ...
Kasra Naftchi‐Ardebili, Karanpartap Singh, Gerald R. Popelka, Kim Butts Pauly   +3 more
wiley   +1 more source

Accelerated water residual removal in MRS: Exploring deep learning versus fitting‐based approaches

Magnetic Resonance in Medicine, Volume 95, Issue 1, Page 38-50, January 2026.
Abstract PurposeRemoving water residual signals from MRS spectra is crucial for accurate metabolite quantification. However, currently available algorithms are computationally intensive and time‐consuming, limiting their clinical applicability. This work aims to propose and validate two novel pipelines for fast water residual removal in MRS. MethodsTwo
Federico Turco, Johannes Slotboom, Milena Capiglioni   +2 more
wiley   +1 more source

Modeling the MRI gradient system with a temporal convolutional network: Improved reconstruction by prediction of readout gradient errors

Magnetic Resonance in Medicine, Volume 95, Issue 1, Page 286-298, January 2026.
Purpose Our objective is to develop a general, nonlinear gradient system model that can accurately predict gradient distortions using convolutional networks. Methods A set of training gradient waveforms were measured on a small animal imaging system and used to train a temporal convolutional network to predict the gradient waveforms produced by the ...
Jonathan B. Martin, Hannah E. Alderson, John C. Gore, Mark D. Does, Kevin D. Harkins   +4 more
wiley   +1 more source

A Hybrid Transformer–CNN Framework for Semantic Behavioral Modeling in Office Malware Detection

SECURITY AND PRIVACY, Volume 9, Issue 1, January/February 2026.
ABSTRACT Office documents have emerged as a prevalent attack vector, with adversaries increasingly embedding executable payloads and malicious macros to evade signature‐based detection mechanisms. To address these challenges, this study presents a hybrid Transformer–CNN semantic behavioral modeling framework for Office malware detection.
Sheikh M. Zeeshan Javed, M. Faisal Amjad, Sajjad A. Ghauri, Shahzaib Tahir, Nauman Anwar Baig   +4 more
wiley   +1 more source

Analysis of High Frequency Marsquake Swarms Informed by Deep Learning

Journal of Geophysical Research: Planets, Volume 131, Issue 1, January 2026.
Abstract NASA's InSight mission has provided an unprecedented snapshot of Mars' seismicity, despite data analysis challenges arising from low signal‐to‐noise ratios (SNR) and single‐station constraints. High frequency (HF) events—the most common type—were initially assumed to propagate through shallow crustal layers.
Nikolaj L. Dahmen, John F. Clinton, Simon C. Stähler, Savas Ceylan, Domenico Giardini   +4 more
wiley   +1 more source

SmartWeed: An Autonomous Rover System for Real‐Time Weed Detection and Classification in Agricultural Fields

IET Cyber-Physical Systems: Theory &Applications, Volume 11, Issue 1, January/December 2026.
This study presents an autonomous rover for real‐time weed detection in agriculture using advanced YOLO object detection models. Experimental results show that YOLOv9‐E achieves the highest accuracy among all models, whereas YOLOv8 variants offer faster processing, demonstrating their potential for efficient and precise weed management in the field ...
Md Shahriar Hossain Apu, Suman Saha
wiley   +1 more source