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As a simple and widely used quantitative phase imaging (QPI) approach, the transport of intensity equation (TIE) is plagued by accuracy and applicability issues due to the limitations of conventional solution algorithms. To address these problems, we present an accurate fast QPI method using an accelerated iteration-based TIE solution. In this method, a gradient acceleration iterative solution is constructed by TIE itself. In this manner, the restrictions in TIE ("phase discrepancy" and "phase singularity" issues) are bypassed, resulting in a fast convergence TIE numerical algorithm with great applicability. In addition, by using high-accurate multi-plane intensity derivative estimation result as initial iteration value, the accuracy and noise robustness of phase reconstruction are significantly improved. Finally, an accurate, fast, and widely applicable QPI can be achieved. Experiments on various phase objects, including phase plates and living cells, demonstrate the accuracy, applicability, and real-time measurement ability of our method. Our method provides a general TIE algorithm for accurate real-time QPI.
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http://dx.doi.org/10.1364/OE.544134 | DOI Listing |
J Strength Cond Res
September 2025
Institute for Data Analysis and Process Design, ZHAW, Zurich, Switzerland; and.
Achermann, BB, Drewek, A, and Lorenzetti, SR. Acute effect of the bounce squat on ground reaction force at the turning point and barbell kinematics. J Strength Cond Res XX(X): 000-000, 2025-The free-weight back squat is a key exercise for developing lower-body strength, with variations that influence muscle activation and performance.
View Article and Find Full Text PDFFront Plant Sci
September 2025
College of Big Data, Yunnan Agricultural University, Kunming, China.
Introduction: Accurate identification of cherry maturity and precise detection of harvestable cherry contours are essential for the development of cherry-picking robots. However, occlusion, lighting variation, and blurriness in natural orchard environments present significant challenges for real-time semantic segmentation.
Methods: To address these issues, we propose a machine vision approach based on the PIDNet real-time semantic segmentation framework.
Int J Hyperthermia
December 2025
Department of Radiation Oncology Physics, University of Maryland, Baltimore, MD, USA.
Objective: To develop a deep learning method for fast and accurate prediction of Specific Absorption Rate (SAR) distributions in the human head to support real-time hyperthermia treatment planning (HTP) of brain cancer patients.
Approach: We propose an encoder-decoder neural network with cross-attention blocks to predict SAR maps from brain electrical properties, tumor 3D isocenter coordinates and microwave antenna phase settings. A dataset of 201 simulations was generated using finite-element modeling by varying tissue properties, tumor positions, and antenna phases within a human head model equipped with a three-ring phased-array applicator.
Eur J Haematol
September 2025
Haematology-Pathology Research Laboratory, Research Unit for Haematology and Research Unit for Pathology, University of Southern Denmark and Odense University Hospital, Odense, Denmark.
Background: Clonotyping of immunoglobulin heavy chain (IGH) gene rearrangements is critical for diagnosis, prognostication, and measurable residual disease monitoring in chronic lymphocytic leukemia (CLL). Although short-read next-generation sequencing (NGS) platforms, such as Illumina MiSeq, are widely used, they face challenges in spanning full VDJ rearrangements. Long-read sequencing via Oxford Nanopore Technologies (ONT) offers a potential alternative using the compact and cost-effective flow cells.
View Article and Find Full Text PDFBiomed Phys Eng Express
September 2025
College of Computer Science and Technology, China University of Petroleum East China - Qingdao Campus, College of Computer Science and Technology, China University of Petroleum (East China), Qingdao 266580, China, Qingdao, Shandong, 266580, CHINA.
Purpose: Cerebrovascular segmentation is crucial for the diagnosis and treatment of cerebrovascular diseases. However, accurately extracting cerebral vessels from Time-of-Flight Magnetic Resonance Angiography (TOF-MRA) remains challenging due to the topological complexity and anatomical variability.
Methods: This paper presents a novel Y-shaped segmentation network with fast Fourier convolution and Mamba, termed F-Mamba-YNet.