Radiomics and its emerging role in lung cancer research, imaging biomarkers and clinical management: State of the art
With the development of functional imaging modalities we now have the ability to study the
microenvironment of lung cancer and its genomic instability. Radiomics is defined as the use …
microenvironment of lung cancer and its genomic instability. Radiomics is defined as the use …
[HTML][HTML] Spatially fractionated radiation therapy: History, present and the future
W Yan, MK Khan, X Wu, CB Simone II, J Fan… - Clinical and translational …, 2020 - Elsevier
Spatially Fractionated Radiation therapy (SFRT) has a history of over 100 years. The
principle of SFRT is distinctive from the standard radiation approaches, as it treats the total …
principle of SFRT is distinctive from the standard radiation approaches, as it treats the total …
Radiological tumour classification across imaging modality and histology
J Wu, C Li, M Gensheimer, S Padda, F Kato… - Nature machine …, 2021 - nature.com
Radiomics refers to the high-throughput extraction of quantitative features from radiological
scans and is widely used to search for imaging biomarkers for the prediction of clinical …
scans and is widely used to search for imaging biomarkers for the prediction of clinical …
Granular multi-label feature selection based on mutual information
F Li, D Miao, W Pedrycz - Pattern Recognition, 2017 - Elsevier
Like the traditional machine learning, the multi-label learning is faced with the curse of
dimensionality. Some feature selection algorithms have been proposed for multi-label …
dimensionality. Some feature selection algorithms have been proposed for multi-label …
Intratumor partitioning and texture analysis of dynamic contrast‐enhanced (DCE)‐MRI identifies relevant tumor subregions to predict pathological response of breast …
Purpose To predict pathological response of breast cancer to neoadjuvant chemotherapy
(NAC) based on quantitative, multiregion analysis of dynamic contrast enhancement …
(NAC) based on quantitative, multiregion analysis of dynamic contrast enhancement …
Recent advances in deep learning and medical imaging for head and neck cancer treatment: MRI, CT, and PET scans
M Illimoottil, D Ginat - Cancers, 2023 - mdpi.com
Simple Summary Deep learning techniques have significant potential in head and neck
cancer imaging, particularly in tumor detection, segmentation, and outcome prediction using …
cancer imaging, particularly in tumor detection, segmentation, and outcome prediction using …
Integrated imaging and molecular analysis to decipher tumor microenvironment in the era of immunotherapy
Radiological imaging is an integral component of cancer care, including diagnosis, staging,
and treatment response monitoring. It contains rich information about tumor phenotypes that …
and treatment response monitoring. It contains rich information about tumor phenotypes that …
Radiomics and radiogenomics for precision radiotherapy
Imaging plays an important role in the diagnosis and staging of cancer, as well as in
radiation treatment planning and evaluation of therapeutic response. Recently, there has …
radiation treatment planning and evaluation of therapeutic response. Recently, there has …
Sub-region based radiomics analysis for survival prediction in oesophageal tumours treated by definitive concurrent chemoradiotherapy
Background Evaluating clinical outcome prior to concurrent chemoradiotherapy remains
challenging for oesophageal squamous cell carcinoma (OSCC) as traditional prognostic …
challenging for oesophageal squamous cell carcinoma (OSCC) as traditional prognostic …
Subregional radiomics analysis of PET/CT imaging with intratumor partitioning: application to prognosis for nasopharyngeal carcinoma
Purpose This work aims to identify intratumoral habitats with distinct heterogeneity based on
2-deoxy-2-[18 F] fluro-d-glucose positron emission tomography (PET)/X-ray computed …
2-deoxy-2-[18 F] fluro-d-glucose positron emission tomography (PET)/X-ray computed …