نتایج جستجو برای: radiomics

تعداد نتایج: 1808  

Journal: :Cellular therapy and transplantation 2022

Применение радиомики в дифференциальной диагностике амелобластом и одонтогенных кист челюстей: часть 2Application of radiomics in the differential diagnosis ameloblastomas and dentigerous cysts. Part 2

2017
Elizabeth J. Sutton Erich P. Huang Karen Drukker Elizabeth S. Burnside Hui Li Jose M. Net Arvind Rao Gary J. Whitman Margarita Zuley Marie Ganott Ermelinda Bonaccio Maryellen L. Giger Elizabeth A. Morris

Background: In this study, we sought to investigate if computer-extracted magnetic resonance imaging (MRI) phenotypes of breast cancer could replicate human-extracted size and Breast Imaging-Reporting and Data System (BI-RADS) imaging phenotypes using MRI data from The Cancer Genome Atlas (TCGA) project of the National Cancer Institute. Methods: Our retrospective interpretation study involved a...

2017
Márton Kolossváry Júlia Karády Bálint Szilveszter Pieter Kitslaar Udo Hoffmann Béla Merkely Pál Maurovich-Horvat

BACKGROUND Napkin-ring sign (NRS) is an independent prognostic imaging marker of major adverse cardiac events. However, identification of NRS is challenging because of its qualitative nature. Radiomics is the process of extracting thousands of quantitative parameters from medical images to create big-data data sets that can identify distinct patterns in radiological images. Therefore, we sought...

Journal: :Journal of Nuclear Medicine 2019

Journal: :International Journal of Radiation Oncology*Biology*Physics 2019

Journal: :Current Cardiovascular Imaging Reports 2022

Abstract Purpose of Review This review the literature aims to present potential applications radiomics in cardiovascular radiology and, particular, cardiac imaging. Recent Findings Radiomics and machine learning represent a technological innovation which may be used extract analyze quantitative features from medical images. They aid detecting hidden pattern data, possibly leading new insights p...

2018
Ahmad Chaddad Paul Daniel Tamim Niazi

Methods: This study investigates multiscale texture features extracted from CRC pathology sections using 3D wavelet transform (3D-WT) filter. Multiscale features were extracted from digital whole slide images of 39 patients that were segmented in a pre-processing step using an active contour model. The capacity for multiscale texture to compare and classify between PTs was investigated using AN...

Journal: :Radiotherapy and Oncology 2019

Journal: :JNCI: Journal of the National Cancer Institute 2020

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