Automated classification of significant prostate cancer on MRI: a systematic review on the performance of machine learning applications
Significant prostate carcinoma (sPCa) classification based on MRI using radiomics or deep
learning approaches has gained much interest, due to the potential application in assisting …
learning approaches has gained much interest, due to the potential application in assisting …
Artificial intelligence in lymphoma PET imaging: a scoping review (current trends and future directions)
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Integrating artificial intelligence into the clinical practice of radiology: challenges and recommendations
Artificial intelligence (AI) has the potential to significantly disrupt the way radiology will be
practiced in the near future, but several issues need to be resolved before AI can be widely …
practiced in the near future, but several issues need to be resolved before AI can be widely …
Assessing robustness of quantitative susceptibility-based MRI radiomic features in patients with multiple sclerosis
C Fiscone, L Rundo, A Lugaresi, DN Manners… - Scientific Reports, 2023 - nature.com
Multiple Sclerosis (MS) is an autoimmune demyelinating disease characterised by changes
in iron and myelin content. These biomarkers are detectable by Quantitative Susceptibility …
in iron and myelin content. These biomarkers are detectable by Quantitative Susceptibility …
Modality-level cross-connection and attentional feature fusion based deep neural network for multi-modal brain tumor segmentation
T Zhou - Biomedical Signal Processing and Control, 2023 - Elsevier
Brain tumor segmentation from Magnetic Resonance Imaging is essential for early diagnosis
and treatment planning for brain cancers in clinical practice. However, existing brain tumor …
and treatment planning for brain cancers in clinical practice. However, existing brain tumor …
Distinguishing pure histopathological growth patterns of colorectal liver metastases on CT using deep learning and radiomics: a pilot study
MPA Starmans, FE Buisman, M Renckens… - Clinical & experimental …, 2021 - Springer
Histopathological growth patterns (HGPs) are independent prognosticators for colorectal
liver metastases (CRLM). Currently, HGPs are determined postoperatively. In this study, we …
liver metastases (CRLM). Currently, HGPs are determined postoperatively. In this study, we …
Radiomics and Artificial Intelligence in Radiotheranostics: a review of applications for Radioligands Targeting somatostatin receptors and prostate-specific membrane …
E Yazdani, P Geramifar, N Karamzade-Ziarati… - Diagnostics, 2024 - mdpi.com
Radiotheranostics refers to the pairing of radioactive imaging biomarkers with radioactive
therapeutic compounds that deliver ionizing radiation. Given the introduction of very …
therapeutic compounds that deliver ionizing radiation. Given the introduction of very …
A machine learning approach to distinguish between knees without and with osteoarthritis using MRI-based radiomic features from tibial bone
Objectives Our aim was to assess the ability of semi-automatically extracted magnetic
resonance imaging (MRI)–based radiomic features from tibial subchondral bone to …
resonance imaging (MRI)–based radiomic features from tibial subchondral bone to …
Toward high-throughput artificial intelligence-based segmentation in oncological PET imaging
An array of artificial intelligence (AI) techniques in the field of medical imaging has emerged
in the past decade for automated image segmentation. 1 Medical image segmentation seeks …
in the past decade for automated image segmentation. 1 Medical image segmentation seeks …
A multi-center, multi-vendor study to evaluate the generalizability of a radiomics model for classifying prostate cancer: high grade vs. low grade
Radiomics applied in MRI has shown promising results in classifying prostate cancer
lesions. However, many papers describe single-center studies without external validation …
lesions. However, many papers describe single-center studies without external validation …