Results 111 to 120 of about 32,314 (198)

MTCA‐Net: Multi‐Task Cascade Analysis Network for Real‐Time Sperm Quality Analysis

Advanced Intelligent Systems, Volume 8, Issue 5, May 2026.
This article proposes MTCA‐Net, a multi‐task cascaded analysis network for real‐time sperm quality assessment in intracytoplasmic sperm injection. The framework integrates detection, tracking, and segmentation modules to jointly analyze sperm morphology and motility.
Jiajin Li, Wenwen Sun, Jun He, Xinyu Fan, Xuecheng Ge, Fengya Lu, Yadan Wang, Yi Wang, Zhiguo Zhang, Qibing Wu, Jinhua Zhou   +10 more
wiley   +1 more source

Enhancing Noise Reduction with Bionic Wavelet and Adaptive Filtering

Inteligencia Artificial
Speech signals often contain different forms of background and environmental noise. For the development of an efficient speech recognition system, it is essential to preprocess noisy speech signals to reduce the impact of these disturbances.
Shraddha C, Chayadevi M L , Anusuya M A , Vani H Y   +3 more
doaj  

Deformable Attention Multiscale Feature Fusion Network‐Dehaze: An Adaptive Image Dehazing Method Based on Deformable Attention Multiscale Fusion Network

Advanced Intelligent Systems, Volume 8, Issue 5, May 2026.
This paper presents the deformable attention multiscale feature fusion network‐dehaze adaptive image dehazing network, which integrates three core modules (revised residual shrinkage unit, multiscale attention, cross‐scale feature fusion). It incorporates deformable convolution and multiscale attention mechanisms to address the detail loss issue of ...
Ruipeng Wang, Yajun Chen, Hao Liu, Mingrui Li, Zhiqi Li   +4 more
wiley   +1 more source

Uncertainty‐aware gamma interaction localization and reconstruction in PET

Medical Physics, Volume 53, Issue 5, May 2026.
Abstract Background Precise localization of gamma‐ray interactions inside scintillation detectors is essential for high‐resolution positron emission tomography (PET) imaging. Although machine learning methods have demonstrated strong performance in gamma interaction positioning, most existing approaches do not quantify event‐level uncertainty, leaving ...
Julian Thull, Jan Remennik, David Schug, Bjoern Weissler, Yannick Kuhl, Volkmar Schulz   +5 more
wiley   +1 more source

High‐Resolution Diffusion‐Weighted Imaging With Self‐Gated Self‐Supervised Unrolled Reconstruction

Magnetic Resonance in Medicine, Volume 95, Issue 5, Page 2852-2862, May 2026.
ABSTRACT Purpose High‐resolution diffusion‐weighted imaging (DWI) is clinically demanding. The purpose of this work is to develop an efficient self‐supervised algorithm unrolling technique for submillimeter‐resolution DWI. Methods We developed submillimeter DWI acquisition utilizing multi‐band multi‐shot EPI with diffusion shift encoding.
Zhengguo Tan, Patrick A. Liebig, Annika Hofmann, Frederik B. Laun, Florian Knoll   +4 more
wiley   +1 more source

T2$$ {\boldsymbol{T}}_{\mathbf{2}} $$‐Weighted Imaging of Water, Fat and Silicone

Magnetic Resonance in Medicine, Volume 95, Issue 5, Page 2765-2775, May 2026.
ABSTRACT Purpose Magnetic resonance imaging (MRI) is a sensitive method for assessing silicone implant integrity, with T2$$ {T}_2 $$‐weighted imaging being essential for detecting abnormalities in surrounding tissue. Silicone breast imaging protocols often require multiple tailored sequences for species suppression and diagnostic contrast. We propose a
Aizada Nurdinova, Xuetong Zhou, Julio A. Oscanoa, Preya Shah, Kawin Setsompop, Bruce L. Daniel, Brian A. Hargreaves   +6 more
wiley   +1 more source

Cross‐Site Generalization of CNN‐Based B1+$$ {B}_1^{+} $$ Mapping in UHF MRI

NMR in Biomedicine, Volume 39, Issue 5, May 2026.
The study demonstrates that CNN%‐based B1+$$ {B}_1^{+} $$ mapping transfers across sites with only moderate accuracy loss: while on‐site RMSEs were as low as ~3%, cross‐site predictions increased errors but remained qualitatively robust. Despite these deviations, cross‐site maps successfully enabled dynamic 4kT‐points pulses, achieving flip‐angle ...
Kimon Hadjikiriakos, Felix Krüger, Felix Frederik Zimmermann, Johannes A. Grimm, Constantin Schorling, Max Lutz, Simon Schmidt, Layla Tabea Riemann, Katja Degenhardt, Tobias Schäffter, Mark E. Ladd, Gregory J. Metzger, Christoph Stefan Aigner, Sebastian Schmitter   +13 more
wiley   +1 more source

Deep Learning Reconstruction Enables Diagnostic‐Quality 0.4T Knee and Spine MRI in One‐Third of the Time

NMR in Biomedicine, Volume 39, Issue 5, May 2026.
The deep learning model CIRIM successfully accelerated knee and spine data up to an acceleration factor of 3, after optimizing the undersampling mask and loss function. The model demonstrated robustness and generalizability to different contrasts, matrix sizes, orientations, and anatomies. ABSTRACT There has been a growing interest in low‐field MRI due
Daisy M. van den Berg, Rosario Varriale, Fabrizio Ferrando, Paolo Traverso, Luca Balbi, Giacomo Belgiorno, Kerensa Beekman, Laura Kox, Gustav J. Strijkers, Matthan W. A. Caan   +9 more
wiley   +1 more source

A PERFORMANCE STUDY OF TWO JPEG COMPRESSION APPROACHES

Journal of Intelligent Systems and Applied Data Science
As technology continues to advance, and the transition into the digital age, we find ourselves dealing with an ever-expanding volume of information, often leading to challenges in management.
Doaa Elmourssi, Wahida A. Mansouri, Wiam A. Elyass, Salwa H. Othman, Somia Asklany   +4 more
doaj  

DEEP‐DISORDER: Motion Correction in 3D MRI via Segment Reconstruction and Registration

NMR in Biomedicine, Volume 39, Issue 5, May 2026.
This work presents a retrospective motion correction framework for 3D MRI. A motion‐corrupted acquisition is split into tiny k‐space segments, and for each a neural network reconstructs a rough anatomical image. These reconstructions are aligned using groupwise registration, yielding one set of estimated motion parameters per segment.
Laurens Beljaards, Martijn Nagtegaal, Chinmay Rao, Yiming Dong, Matthias J. P. van Osch, Nicola Pezzotti, Mariya Doneva, Marius Staring   +7 more
wiley   +1 more source