Radiomics-driven spectral profiling of six kidney stone types with monoenergetic CT reconstructions in photon-counting CT
A Hertel, MF Froelich, D Overhoff, T Nestler, S Faby… - European …, 2024 - Springer
Objectives Urolithiasis, a common and painful urological condition, is influenced by factors
such as lifestyle, genetics, and medication. Differentiating between different types of kidney …
such as lifestyle, genetics, and medication. Differentiating between different types of kidney …
Differentiation of granulomatous nodules with lobulation and spiculation signs from solid lung adenocarcinomas using a CT deep learning model
Y Wen, W Wu, Y Liufu, X Pan, Y Zhang, S Qi, Y Guan - BMC cancer, 2024 - Springer
Background The diagnosis of solitary pulmonary nodules has always been a difficult and
important point in clinical research, especially granulomatous nodules (GNs) with lobulation …
important point in clinical research, especially granulomatous nodules (GNs) with lobulation …
Machine Learning and Radiomics Analysis for Tumor Budding Prediction in Colorectal Liver Metastases Magnetic Resonance Imaging Assessment
Purpose: We aimed to assess the efficacy of machine learning and radiomics analysis using
magnetic resonance imaging (MRI) with a hepatospecific contrast agent, in a pre-surgical …
magnetic resonance imaging (MRI) with a hepatospecific contrast agent, in a pre-surgical …
Deep Learning Radiomics Model of Contrast-Enhanced CT for Differentiating the Primary Source of Liver Metastases
W Jia, F Li, Y Cui, Y Wang, Z Dai, Q Yan, X Liu, Y Li… - Academic …, 2024 - Elsevier
Rationale and Objectives To develop and validate a deep learning radiomics (DLR) model
based on contrast-enhanced computed tomography (CT) to identify the primary source of …
based on contrast-enhanced computed tomography (CT) to identify the primary source of …
CT-based liver peritumoural radiomics features predict hepatic metastases sources as gastrointestinal or non-gastrointestinal
C Hou, F Wang, M Prince, X Yang… - British Journal of …, 2024 - academic.oup.com
Objectives To investigate the feasibility of radiomics models for predicting the source of
hepatic metastases from gastrointestinal (GI) vs non-gastrointestinal (non-GI) primary …
hepatic metastases from gastrointestinal (GI) vs non-gastrointestinal (non-GI) primary …
Textural heterogeneity of liver lesions in CT imaging-comparison of colorectal and pancreatic metastases
FL Pietsch, F Haag, I Ayx, F Grawe, AK Vellala… - Abdominal …, 2024 - Springer
Purpose Tumoral heterogeneity poses a challenge for personalized cancer treatments.
Especially in metastasized cancer, it remains a major limitation for successful targeted …
Especially in metastasized cancer, it remains a major limitation for successful targeted …
Elucidating the novel framework of liver tumour segmentation and classification using improved Optimization-assisted EfficientNet B7 learning model
S Dharaneswar, BPS Kumar - Biomedical Signal Processing and Control, 2025 - Elsevier
Liver cancer is an important disease that leads to the death of people worldwide. Image
classification based on Computed Axial Tomography (CAT) and manual segmentation is the …
classification based on Computed Axial Tomography (CAT) and manual segmentation is the …
SRFAMap: A Method for Mapping Integrated Gradients of a CNN Trained with Statistical Radiomic Features to Medical Image Saliency Maps
Many explainable AI methods for generating medical image saliency maps exist, but most
are devoted to working on trained neural network-based models. At the same time, many …
are devoted to working on trained neural network-based models. At the same time, many …
Applications of Artificial Intelligence in Screening, Diagnosis, Treatment, and Prediction of Prognosis of Colorectal Cancer
A Pourshams, SG Sepanlou - GOVARESH, 2024 - govaresh.org
Colorectal cancer (CRC) is one of the most common cancers globally. Prevention, precise
early detection and diagnosis, selecting the best treatment strategy, and correct prediction of …
early detection and diagnosis, selecting the best treatment strategy, and correct prediction of …
[PDF][PDF] Classification of Liver Lesion Stages using pyRadiomics Features Combined with 3D-CNN in 3D-CT and US Images
AB Parimala… - Indian Journal …, 2024 - sciresol.s3.us-east-2.amazonaws …
Objectives: The goal of this study is to identify the various stages in liver diseases employing
pyRadiomics features by analyzing the 3-dimensional CT and US images. Methods: The …
pyRadiomics features by analyzing the 3-dimensional CT and US images. Methods: The …