Computer methods and programs in biomedicine
May 22, 2022
BACKGROUND AND OBJECTIVE: In oncology, 18-fluorodeoxyglucose (F-FDG) positron emission tomography (PET) / computed tomography (CT) is widely used to identify and analyse metabolically-active tumours. The combination of the high sensitivity and specif...
Liver international : official journal of the International Association for the Study of the Liver
May 5, 2022
BACKGROUND AND AIMS: Radiological prediction of microvascular invasion (MVI) of hepatocellular carcinoma (HCC) is essential but few models were clinically implemented because of limited interpretability and generalizability.
OBJECTIVE: To examine whether the machine-learning approach using 18-fludeoxyglucose positron emission tomography (F-FDG-PET)-based radiomic and deep-learning features is useful for predicting the pathological risk subtypes of thymic epithelial tumor...
European journal of nuclear medicine and molecular imaging
Mar 12, 2022
UNLABELLED: A novel deep learning (DL)-based attenuation correction (AC) framework was applied to clinical whole-body oncology studies using F-FDG, Ga-DOTATATE, and F-Fluciclovine. The framework used activity (λ-MLAA) and attenuation (µ-MLAA) maps e...
Journal of nuclear medicine : official publication, Society of Nuclear Medicine
Mar 3, 2022
The objective of this study was to evaluate the safety and feasibility of Tc-based prostate-specific membrane antigen (PSMA) robot-assisted-radioguided surgery to aid or improve the intraoperative detection of lymph node metastases during primary rob...
OBJECTIVE: It is important to detect parathyroid adenomas by parathyroid scintigraphy with 99m-technetium sestamibi (Tc-MIBI) before surgery. This study aimed to develop and validate deep learning (DL)-based models to detect parathyroid adenoma in pa...
Artificial intelligence (AI) can be applied to head and neck imaging to augment image quality and various clinical tasks including segmentation of tumor volumes, tumor characterization, tumor prognostication and treatment response, and prediction of ...
To evaluate the performance of a deep convolutional neural network (DCNN) in detecting local tumor progression (LTP) after tumor ablation for hepatocellular carcinoma (HCC) on follow-up arterial phase CT images. The DCNN model utilizes three-dimensio...
PURPOSE: To develop an anomaly detection system in PET/CT with the tracer F-fluorodeoxyglucose (FDG) that requires only normal PET/CT images for training and can detect abnormal FDG uptake at any location in the chest region.
PURPOSE: The purpose of this work was to develop and validate a deep convolutional neural network (CNN) approach for the automated pelvis segmentation in computed tomography (CT) scans to enable the quantification of active pelvic bone marrow by mean...