Artificial intelligence and machine learning in cancer imaging
An increasing array of tools is being developed using artificial intelligence (AI) and machine
learning (ML) for cancer imaging. The development of an optimal tool requires …
learning (ML) for cancer imaging. The development of an optimal tool requires …
Application of artificial intelligence in diagnosis and treatment of colorectal cancer: A novel Prospect
Z Yin, C Yao, L Zhang, S Qi - Frontiers in Medicine, 2023 - frontiersin.org
In the past few decades, according to the rapid development of information technology,
artificial intelligence (AI) has also made significant progress in the medical field. Colorectal …
artificial intelligence (AI) has also made significant progress in the medical field. Colorectal …
Medical image segmentation on mri images with missing modalities: A review
R Azad, N Khosravi, M Dehghanmanshadi… - arXiv preprint arXiv …, 2022 - arxiv.org
Dealing with missing modalities in Magnetic Resonance Imaging (MRI) and overcoming
their negative repercussions is considered a hurdle in biomedical imaging. The combination …
their negative repercussions is considered a hurdle in biomedical imaging. The combination …
MRI radiomics independent of clinical baseline characteristics and neoadjuvant treatment modalities predicts response to neoadjuvant therapy in rectal cancer
M Song, S Li, H Wang, K Hu, F Wang, H Teng… - British Journal of …, 2022 - nature.com
Background To analyse the performance of multicentre pre-treatment MRI-based radiomics
(MBR) signatures combined with clinical baseline characteristics and neoadjuvant treatment …
(MBR) signatures combined with clinical baseline characteristics and neoadjuvant treatment …
Analysis of MRI and CT-based radiomics features for personalized treatment in locally advanced rectal cancer and external validation of published radiomics models
I Shahzadi, A Zwanenburg, A Lattermann, A Linge… - Scientific reports, 2022 - nature.com
Radiomics analyses commonly apply imaging features of different complexity for the
prediction of the endpoint of interest. However, the prognostic value of each feature class is …
prediction of the endpoint of interest. However, the prognostic value of each feature class is …
Contemporary management of locally advanced and recurrent rectal cancer: views from the PelvEx Collaborative
PelvEx Collaborative - Cancers, 2022 - mdpi.com
Simple Summary Pelvic exenteration is a complex procedure performed for the
management of advanced pelvic cancers. It often involves the resection of several pelvic …
management of advanced pelvic cancers. It often involves the resection of several pelvic …
Endorectal ultrasound radiomics in locally advanced rectal cancer patients: despeckling and radiotherapy response prediction using machine learning
S Abbaspour, H Abdollahi, H Arabalibeik… - Abdominal …, 2022 - Springer
Purpose The current study aimed to evaluate the association of endorectal ultrasound (EUS)
radiomics features at different denoising filters based on machine learning algorithms and to …
radiomics features at different denoising filters based on machine learning algorithms and to …
MRI-based radiomics to predict response in locally advanced rectal cancer: comparison of manual and automatic segmentation on external validation in a multicentre …
A Defeudis, S Mazzetti, J Panic, M Micilotta… - European Radiology …, 2022 - Springer
Background Pathological complete response after neoadjuvant chemoradiotherapy in
locally advanced rectal cancer (LARC) is achieved in 15–30% of cases. Our aim was to …
locally advanced rectal cancer (LARC) is achieved in 15–30% of cases. Our aim was to …
Preoperative prediction of extramural venous invasion in rectal cancer by dynamic contrast-enhanced and diffusion weighted MRI: a preliminary study
W Ao, X Zhang, X Yao, X Zhu, S Deng, J Feng - BMC Medical Imaging, 2022 - Springer
Background To explore the value of the quantitative dynamic contrast-enhanced magnetic
resonance imaging (DCE-MRI) and diffusion-weighted imaging (DWI) parameters in …
resonance imaging (DCE-MRI) and diffusion-weighted imaging (DWI) parameters in …
Radiomics-based machine learning differentiates “ground-glass” opacities due to COVID-19 from acute non-COVID-19 lung disease
A Delli Pizzi, AM Chiarelli, P Chiacchiaretta… - Scientific reports, 2021 - nature.com
Ground-glass opacities (GGOs) are a non-specific high-resolution computed tomography
(HRCT) finding tipically observed in early Coronavirus disesase 19 (COVID-19) pneumonia …
(HRCT) finding tipically observed in early Coronavirus disesase 19 (COVID-19) pneumonia …