Machine and deep learning methods for radiomics
Radiomics is an emerging area in quantitative image analysis that aims to relate large‐scale
extracted imaging information to clinical and biological endpoints. The development of …
extracted imaging information to clinical and biological endpoints. The development of …
Biobanking in health care: evolution and future directions
L Coppola, A Cianflone, AM Grimaldi… - Journal of translational …, 2019 - Springer
Background The aim of the present review is to discuss how the promising field of
biobanking can support health care research strategies. As the concept has evolved over …
biobanking can support health care research strategies. As the concept has evolved over …
Radiomics in prostate cancer: An up-to-date review
M Ferro, O de Cobelli, G Musi… - Therapeutic …, 2022 - journals.sagepub.com
Prostate cancer (PCa) is the most common worldwide diagnosed malignancy in male
population. The diagnosis, the identification of aggressive disease, and the post-treatment …
population. The diagnosis, the identification of aggressive disease, and the post-treatment …
Prostate cancer radiogenomics—from imaging to molecular characterization
M Ferro, O de Cobelli, MD Vartolomei… - International Journal of …, 2021 - mdpi.com
Radiomics and genomics represent two of the most promising fields of cancer research,
designed to improve the risk stratification and disease management of patients with prostate …
designed to improve the risk stratification and disease management of patients with prostate …
Multiparametric MRI and radiomics in prostate cancer: a review
Y Sun, HM Reynolds, B Parameswaran… - Australasian physical & …, 2019 - Springer
Multiparametric MRI (mpMRI) is an imaging modality that combines anatomical MR imaging
with one or more functional MRI sequences. It has become a versatile tool for detecting and …
with one or more functional MRI sequences. It has become a versatile tool for detecting and …
[HTML][HTML] Novel, non-invasive imaging approach to identify patients with advanced non-small cell lung cancer at risk of hyperprogressive disease with immune …
Purpose Hyperprogression is an atypical response pattern to immune checkpoint inhibition
that has been described within non-small cell lung cancer (NSCLC). The paradoxical …
that has been described within non-small cell lung cancer (NSCLC). The paradoxical …
Machine and deep learning prediction of prostate cancer aggressiveness using multiparametric MRI
E Bertelli, L Mercatelli, C Marzi, E Pachetti… - Frontiers in …, 2022 - frontiersin.org
Prostate cancer (PCa) is the most frequent male malignancy and the assessment of PCa
aggressiveness, for which a biopsy is required, is fundamental for patient management …
aggressiveness, for which a biopsy is required, is fundamental for patient management …
The added value of PSMA PET/MR radiomics for prostate cancer staging
Purpose To evaluate the performance of combined PET and multiparametric MRI (mpMRI)
radiomics for the group-wise prediction of postsurgical Gleason scores (psGSs) in primary …
radiomics for the group-wise prediction of postsurgical Gleason scores (psGSs) in primary …
Machine learning-based radiomic models to predict intensity-modulated radiation therapy response, Gleason score and stage in prostate cancer
Objective To develop different radiomic models based on the magnetic resonance imaging
(MRI) radiomic features and machine learning methods to predict early intensity-modulated …
(MRI) radiomic features and machine learning methods to predict early intensity-modulated …
Radiomics features measured with multiparametric magnetic resonance imaging predict prostate cancer aggressiveness
Purpose: We sought to 1) assess the association of radiomics features based on
multiparametric magnetic resonance imaging with histopathological Gleason score, gene …
multiparametric magnetic resonance imaging with histopathological Gleason score, gene …