Radiomics of the paranasal sinuses: A systematic review of computer-assisted techniques to assess computed tomography radiological data
R Darbari Kaul, PL Sacks, C Thiel… - American Journal of …, 2024 - journals.sagepub.com
Background Radiomics is a quantitative approach to medical imaging, aimed to extract
features into large datasets. By using artificial intelligence (AI) methodologies, large …
features into large datasets. By using artificial intelligence (AI) methodologies, large …
[HTML][HTML] Decoding Radiomics: A Step-by-Step Guide to Machine Learning Workflow in Hand-Crafted and Deep Learning Radiomics Studies
M Cè, MD Chiriac, A Cozzi, L Macrì, FL Rabaiotti… - Diagnostics, 2024 - mdpi.com
Although radiomics research has experienced rapid growth in recent years, with numerous
studies dedicated to the automated extraction of diagnostic and prognostic information from …
studies dedicated to the automated extraction of diagnostic and prognostic information from …
[HTML][HTML] radmlbench: A dataset collection for benchmarking in radiomics
A Demircioğlu - Computers in Biology and Medicine, 2024 - Elsevier
Background New machine learning methods and techniques are frequently introduced in
radiomics, but they are often tested on a single dataset, which makes it challenging to …
radiomics, but they are often tested on a single dataset, which makes it challenging to …
Different radiomics annotation methods comparison in rectal cancer characterisation and prognosis prediction: a two-centre study
Y Zhu, Y Wei, Z Chen, X Li, S Zhang, C Wen, G Cao… - Insights into …, 2024 - Springer
Objectives To explore the performance differences of multiple annotations in radiomics
analysis and provide a reference for tumour annotation in large-scale medical image …
analysis and provide a reference for tumour annotation in large-scale medical image …
Coupling AI and Citizen Science in Creation of Enhanced Training Dataset for Medical Image Segmentation
Recent advancements in medical imaging and artificial intelligence (AI) have greatly
enhanced diagnostic capabilities, but the development of effective deep learning (DL) …
enhanced diagnostic capabilities, but the development of effective deep learning (DL) …
-New frontiers in domain-inspired radiomics and radiogenomics: increasing role of molecular diagnostics in CNS tumor classification and grading following WHO CNS …
Gliomas and Glioblastomas represent a significant portion of central nervous system (CNS)
tumors associated with high mortality rates and variable prognosis. In 2021, the World …
tumors associated with high mortality rates and variable prognosis. In 2021, the World …