This study used explainable artificial intelligence for data-driven identification of extrastriatal brain regions that can contribute to the interpretation of dopamine transporter SPECT with I-FP-CIT in parkinsonian syndromes. A total of 1306 I-FP-CI...
BACKGROUND: Tc-pertechnetate thyroid scintigraphy is a valid complementary avenue for evaluating thyroid disease in the clinic, the image feature of thyroid scintigram is relatively simple but the interpretation still has a moderate consistency among...
OBJECTIVE: To assess the clinical practicability of the ensemble learning model established by Liu et al. in estimating glomerular filtration rate (GFR) and validate whether it is a better model than the Asian modified Chronic Kidney Disease Epidemio...
Novel diagnostic and therapeutic radiopharmaceuticals are increasingly becoming a central part of personalized medicine. Continued innovation in the development of new radiopharmaceuticals is key to sustained growth and advancement of precision medic...
BACKGROUND & AIMS: Body composition analysis on CT images is a valuable tool for sarcopenia assessment. We aimed to develop and validate a deep neural network applicable to whole-body CT images of PET-CT scan for the automatic volumetric segmentation...
Artificial intelligence, including deep learning, is currently revolutionising the field of medical imaging, with far reaching implications for almost every facet of diagnostic imaging, including patient radiation safety. This paper introduces basic ...
In a time of rapid advances in science and technology, the opportunities for radiation oncology are undergoing transformational change. The linkage between and understanding of the physical dose and induced biological perturbations are opening entire...
To develop an artificial intelligence (AI)-based method for the detection of focal skeleton/bone marrow uptake (BMU) in patients with Hodgkin's lymphoma (HL) undergoing staging with FDG-PET/CT. The results of the AI in a separate test group were comp...
Clinical cancer research : an official journal of the American Association for Cancer Research
May 4, 2021
PURPOSE: Accurate prognostic stratification of patients with oropharyngeal squamous cell carcinoma (OPSCC) is crucial. We developed an objective and robust deep learning-based fully-automated tool called the DeepPET-OPSCC biomarker for predicting ove...