AI Medical Compendium Journal:
Cancer imaging : the official publication of the International Cancer Imaging Society

Showing 51 to 60 of 62 articles

Predicting microvascular invasion in hepatocellular carcinoma: a deep learning model validated across hospitals.

Cancer imaging : the official publication of the International Cancer Imaging Society
BACKGROUND: The accuracy of estimating microvascular invasion (MVI) preoperatively in hepatocellular carcinoma (HCC) by clinical observers is low. Most recent studies constructed MVI predictive models utilizing radiological and/or radiomics features ...

Deep learning for semi-automated unidirectional measurement of lung tumor size in CT.

Cancer imaging : the official publication of the International Cancer Imaging Society
BACKGROUND: Performing Response Evaluation Criteria in Solid Tumor (RECISTS) measurement is a non-trivial task requiring much expertise and time. A deep learning-based algorithm has the potential to assist with rapid and consistent lesion measurement...

Differentiating IDH status in human gliomas using machine learning and multiparametric MR/PET.

Cancer imaging : the official publication of the International Cancer Imaging Society
BACKGROUND: The purpose of this study was to develop a voxel-wise clustering method of multiparametric magnetic resonance imaging (MRI) and 3,4-dihydroxy-6-[F]-fluoro-L-phenylalanine (FDOPA) positron emission tomography (PET) images using an unsuperv...

Radiomics for glioblastoma survival analysis in pre-operative MRI: exploring feature robustness, class boundaries, and machine learning techniques.

Cancer imaging : the official publication of the International Cancer Imaging Society
BACKGROUND: This study aims to identify robust radiomic features for Magnetic Resonance Imaging (MRI), assess feature selection and machine learning methods for overall survival classification of Glioblastoma multiforme patients, and to robustify mod...

Multi-view secondary input collaborative deep learning for lung nodule 3D segmentation.

Cancer imaging : the official publication of the International Cancer Imaging Society
BACKGROUND: Convolutional neural networks (CNNs) have been extensively applied to two-dimensional (2D) medical image segmentation, yielding excellent performance. However, their application to three-dimensional (3D) nodule segmentation remains a chal...

Preoperative assessment of lymph node metastasis in Colon Cancer patients using machine learning: a pilot study.

Cancer imaging : the official publication of the International Cancer Imaging Society
BACKGROUND: Preoperative detection of lymph node (LN) metastasis is critical for planning treatments in colon cancer (CC). The clinical diagnostic criteria based on the size of the LNs are not sensitive to determine metastasis using CT images. In thi...

Independent validation of machine learning in diagnosing breast Cancer on magnetic resonance imaging within a single institution.

Cancer imaging : the official publication of the International Cancer Imaging Society
BACKGROUND: As artificial intelligence methods for the diagnosis of disease advance, we aimed to evaluate machine learning in the predictive task of distinguishing between malignant and benign breast lesions on an independent clinical magnetic resona...

Deep learning networks find unique mammographic differences in previous negative mammograms between interval and screen-detected cancers: a case-case study.

Cancer imaging : the official publication of the International Cancer Imaging Society
BACKGROUND: To determine if mammographic features from deep learning networks can be applied in breast cancer to identify groups at interval invasive cancer risk due to masking beyond using traditional breast density measures.

Application of a machine learning method to whole brain white matter injury after radiotherapy for nasopharyngeal carcinoma.

Cancer imaging : the official publication of the International Cancer Imaging Society
BACKGROUND: The purpose/aim of this study was to 1) use magnetic resonance diffusion tensor imaging (DTI), fibre bundle/tract-based spatial statistics (TBSS) and machine learning methods to study changes in the white matter (WM) structure and whole b...

Ga PSMA-11 PET with CT urography protocol in the initial staging and biochemical relapse of prostate cancer.

Cancer imaging : the official publication of the International Cancer Imaging Society
BACKGROUND: Ga-labelled prostate specific membrane antigen (PSMA) ligand PET/CT is a promising modality in primary staging (PS) and biochemical relapse (BCR) of prostate cancer (PC). However, pelvic nodes or local recurrences can be difficult to diff...