Results 61 to 70 of about 1,826,590 (358)

Intrinsic Respiratory Gating for Simultaneous Multi-Mouse μCT Imaging to Assess Liver Tumors

Frontiers in Medicine, 2022
Small animal micro computed tomography (μCT) is an important tool in cancer research and is used to quantify liver and lung tumors. A type of cancer that is intensively investigated with μCT is hepatocellular carcinoma (HCC).
Mirko Thamm, Mirko Thamm, Stefanie Rosenhain, Kevin Leonardic, Andreas Höfter, Fabian Kiessling, Fabian Kiessling, Franz Osl, Thomas Pöschinger, Felix Gremse, Felix Gremse   +10 more
doaj   +1 more source

High-speed tensor tomography: iterative reconstruction tensor tomography (IRTT) algorithm

Acta Crystallographica Section A: Foundations and Advances, 2019
A fast and robust reconstruction algorithm for small-angle scattering tensor tomography, named iterative reconstruction tensor tomography, is presented.
Zirui Gao, M. Guizar‐Sicairos, V. Lutz-Bueno, A. Schröter, M. Liebi, M. Rudin, M. Georgiadis   +6 more
semanticscholar   +1 more source

Classification of acute myeloid leukemia based on multi‐omics and prognosis prediction value

Molecular Oncology, EarlyView.
The Unsupervised AML Multi‐Omics Classification System (UAMOCS) integrates genomic, methylation, and transcriptomic data to categorize AML patients into three subtypes (UAMOCS1‐3). This classification reveals clinical relevance, highlighting immune and chromosomal characteristics, prognosis, and therapeutic vulnerabilities.
Yang Song, Zhe Wang, Guangji Zhang, Jiangxue Hou, Kaiqi Liu, Shuning Wei, Yan Li, Chunlin Zhou, Dong Lin, Min Wang, Hui Wei, Jianxiang Wang, Tao Cheng, Yingchang Mi   +13 more
wiley   +1 more source

Breakthrough Solution for Antimicrobial Resistance Detection: Surface‐Enhanced Raman Spectroscopy‐based on Artificial Intelligence

Advanced Materials Interfaces, EarlyView., 2023
This review discusses the use of Surface‐Enhanced Raman Spectroscopy (SERS) combined with Artificial Intelligence (AI) for detecting antimicrobial resistance (AMR). Various SERS studies used with AI techniques, including machine learning and deep learning, are analyzed for their advantages and limitations.
Zakarya Al‐Shaebi, Munevver Akdeniz, Awel Olsido Ahmed, Mine Altunbek, Omer Aydin   +4 more
wiley   +1 more source

Analytic time-of-flight positron emission tomography reconstruction: two-dimensional case

Visual Computing for Industry, Biomedicine, and Art, 2019
In a positron emission tomography (PET) scanner, the time-of-flight (TOF) information gives us rough event position along the line-of-response (LOR). Using the TOF information for PET image reconstruction is able to reduce image noise.
Gengsheng L. Zeng, Ya Li, Qiu Huang
doaj   +1 more source

Extension of emission expectation maximization lookalike algorithms to Bayesian algorithms

Visual Computing for Industry, Biomedicine, and Art, 2019
We recently developed a family of image reconstruction algorithms that look like the emission maximum-likelihood expectation-maximization (ML-EM) algorithm. In this study, we extend these algorithms to Bayesian algorithms.
Gengsheng L. Zeng, Ya Li
doaj   +1 more source

Non-iterative image reconstruction from sparse magnetic resonance imaging radial data without priors

Visual Computing for Industry, Biomedicine, and Art, 2020
The state-of-the-art approaches for image reconstruction using under-sampled k-space data are compressed sensing based. They are iterative algorithms that optimize objective functions with spatial and/or temporal constraints.
Gengsheng L. Zeng, Edward V. DiBella
doaj   +1 more source

Application of Energy Spectrum Purification Combined with Iterative Reconstruction Algorithm in Low-dose CT Examination of Patients with Secondary Pulmonary Tuberculosis

CT Lilun yu yingyong yanjiu, 2022
Objective: To explore the application of energy spectrum purification combined with iterative reconstruction algorithm in low-dose CT examination of patients with secondary pulmonary tuberculosis.
Yi JIANG, Kui TIAN, Jinlu SHA, Lixin QIN
doaj   +1 more source

Iterative PET Image Reconstruction Using Convolutional Neural Network Representation [PDF]

IEEE Transactions on Medical Imaging, 2017
PET image reconstruction is challenging due to the ill-poseness of the inverse problem and limited number of detected photons. Recently, the deep neural networks have been widely and successfully used in computer vision tasks and attracted growing ...
Kuang Gong, Jiahui Guan, Kyungsang Kim, Xuezhu Zhang, Jaewon Yang, Youngho Seo, G. El Fakhri, J. Qi, Quanzheng Li   +8 more
semanticscholar   +1 more source

An approach for coherent periodogram averaging of tilt‐series data for improved contrast transfer function estimation

FEBS Open Bio, EarlyView.
The contrast transfer function (CTF) is an imaging aberration that is a major resolution‐limiting factor in cryo‐electron microscopy (cryo‐EM). Precise CTF estimation is key to overcoming this limitation, but is particularly challenging in cryo‐electron tomography (cryo‐ET) data. Here, we present an approach for using geometric information to assist in
Sagar Khavnekar, William Wan
wiley   +1 more source