Results 31 to 40 of about 82,903 (262)

Lung radiomics features for characterizing and classifying COPD stage based on feature combination strategy and multi-layer perceptron classifier

Mathematical Biosciences and Engineering, 2022
Computed tomography (CT) has been the most effective modality for characterizing and quantifying chronic obstructive pulmonary disease (COPD). Radiomics features extracted from the region of interest in chest CT images have been widely used for lung ...
Yingjian Yang , Wei Li , Yingwei Guo , Nanrong Zeng, Shicong Wang , Ziran Chen, Yang Liu, Huai Chen, Wenxin Duan, Xian Li , Wei Zhao, Rongchang Chen , Yan Kang   +12 more
doaj   +1 more source

Precise enhancement quantification in post-operative MRI as an indicator of residual tumor impact is associated with survival in patients with glioblastoma

Scientific Reports, 2021
Glioblastoma is the most common primary brain tumor. Standard therapy consists of maximum safe resection combined with adjuvant radiochemotherapy followed by chemotherapy with temozolomide, however prognosis is extremely poor.
Alonso Garcia-Ruiz, Pablo Naval-Baudin, Marta Ligero, Albert Pons-Escoda, Jordi Bruna, Gerard Plans, Nahum Calvo, Monica Cos, Carles Majós, Raquel Perez-Lopez   +9 more
doaj   +1 more source

Computational Radiomics System to Decode the Radiographic Phenotype.

Cancer Research, 2017
Radiomics aims to quantify phenotypic characteristics on medical imaging through the use of automated algorithms. Radiomic artificial intelligence (AI) technology, either based on engineered hard-coded algorithms or deep learning methods, can be used to ...
Joost J. M. van Griethuysen, Andrey Fedorov, C. Parmar, A. Hosny, Nicole Aucoin, V. Narayan, R. Beets-Tan, J. Fillion-Robin, S. Pieper, H. Aerts   +9 more
semanticscholar   +1 more source

Tensor Radiomics: Paradigm for Systematic Incorporation of Multi-Flavoured Radiomics Features

SSRN Electronic Journal, 2022
Radiomics features extract quantitative information from medical images, towards the derivation of biomarkers for clinical tasks, such as diagnosis, prognosis, or treatment response assessment. Different image discretization parameters (e.g. bin number or size), convolutional filters, segmentation perturbation, or multi-modality fusion levels can be ...
Rahmim, Arman, Toosi, Amirhosein, Salmanpour, Mohammad R., Dubljevic, Natalia, Janzen, Ian, Shiri Lord, Isaac, Yuan, Ren, Ho, Cheryl, Zaidi, Habib, MacAulay, Calum, Uribe, Carlos, Yousefirizi, Fereshteh   +11 more
openaire   +4 more sources

How Radiomics Can Improve Breast Cancer Diagnosis and Treatment

Journal of Clinical Medicine, 2023
Recent technological advances in the field of artificial intelligence hold promise in addressing medical challenges in breast cancer care, such as early diagnosis, cancer subtype determination and molecular profiling, prediction of lymph node metastases,
F. Pesapane, P. De Marco, Anna Rapino, Eleonora Lombardo, L. Nicosia, P. Tantrige, A. Rotili, A. Bozzini, S. Penco, V. Dominelli, C. Trentin, F. Ferrari, Mariagiorgia Farina, L. Meneghetti, A. Latronico, F. Abbate, D. Origgi, G. Carrafiello, E. Cassano   +18 more
semanticscholar   +1 more source

MRI radiomic features are independently associated with overall survival in soft tissue sarcoma [PDF]

, 2019
Purpose: Soft tissue sarcomas (STS) represent a heterogeneous group of diseases, and selection of individualized treatments remains a challenge. The goal of this study was to determine whether radiomic features extracted from magnetic resonance (MR ...
Ball, Kevin C, Chapman, Tobias R, Combs, Stephanie E, Hippe, Daniel S, Hoff, Michael N, Kim, Edward Y, Macomber, Meghan W, Nyflot, Matthew J, Peeken, Jan C, Pollack, Seth M, Spraker, Matthew B, Wootton, Landon S   +11 more
core   +2 more sources

Exploring the efficacy of multi-flavored feature extraction with radiomics and deep features for prostate cancer grading on mpMRI

BMC Medical Imaging, 2023
Background The purpose of this study is to investigate the use of radiomics and deep features obtained from multiparametric magnetic resonance imaging (mpMRI) for grading prostate cancer.
Hasan Khanfari, Saeed Mehranfar, Mohsen Cheki, Mahmoud Mohammadi Sadr, Samir Moniri, Sahel Heydarheydari, S. M. Rezaeijo   +6 more
semanticscholar   +1 more source

Radiomics in the diagnosis of glioblastoma

Polish Journal of Radiology, 2023
Radiomics is a process of extracting many quantitative data obtained from medical images and analysing them. In neuroradiology it may be used to discover magnetic resonance imaging (MRI) features of glioblastomas that are impossible to identify by human vision alone.
Kwiatkowska-Miernik, Agnieszka, Mruk, Bartosz, Sklinda, Katarzyna, Zaczyński, Artur, Walecki, Jerzy   +4 more
openaire   +2 more sources

Exploring the Value of Radiomics Features Based on B-Mode and Contrast-Enhanced Ultrasound in Discriminating the Nature of Thyroid Nodules

Frontiers in Oncology, 2021
BackgroundWith the improvement of ultrasound imaging resolution and the application of various new technologies, the detection rate of thyroid nodules has increased greatly in recent years. However, there are still challenges in accurately diagnosing the
Shi Yan Guo, Ping Zhou, Yan Zhang, Li Qing Jiang, Yong Feng Zhao   +4 more
doaj   +1 more source

Radiomics: Images Are More than Pictures, They Are Data

Radiology, 2015
This report describes the process of radiomics, its challenges, and its potential power to facilitate better clinical decision making, particularly in the care of patients with cancer.
R. Gillies, Paul Kinahan, H. Hricak
semanticscholar   +1 more source