Bone cancer originates from bone and rapidly spreads to the rest of the body affecting the patient. A quick and preliminary diagnosis of bone cancer begins with the analysis of bone X-ray or MRI image. Compared to MRI, an X-ray image provides a low-c...
Journal of vascular and interventional radiology : JVIR
Mar 1, 2019
PURPOSE: To construct the albumin-bilirubin (ALBI) grade and the Child-Turcotte-Pugh (CTP) score based on nomograms, as well as to develop an artificial neural network (ANN) to compare the prognostic performance of the 2 scores for hepatocellular car...
Technology in cancer research & treatment
Jan 1, 2019
Radiotherapy is the main treatment strategy for nasopharyngeal carcinoma. A major factor affecting radiotherapy outcome is the accuracy of target delineation. Target delineation is time-consuming, and the results can vary depending on the experience ...
Zhong nan da xue xue bao. Yi xue ban = Journal of Central South University. Medical sciences
Dec 28, 2018
To explore the feasibility and efficacy of artificial neural network for differentiating high-grade glioma and low-grade glioma using image information. Methods: A total of 130 glioma patients with confirmed pathological diagnosis were selected retr...
PURPOSE: Nuclear pleomorphic patterns are essential for Fuhrman grading of clear cell renal cell carcinoma (ccRCC). Manual observation of renal histopathologic slides may lead to subjective and inconsistent assessment between pathologists. An automat...
OBJECTIVEPrognostication and surgical planning for WHO grade I versus grade II meningioma requires thoughtful decision-making based on radiographic evidence, among other factors. Although conventional statistical models such as logistic regression ar...
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2018
Aberration in tissue architecture is an essential index for cancer diagnosis and tumor grading. Therefore, extracting features of aberrant phenotypes and classification of the histology tissue can provide a model for computer-aided pathology (CAP). A...
Current machine learning techniques provide the opportunity to develop noninvasive and automated glioma grading tools, by utilizing quantitative parameters derived from multi-modal magnetic resonance imaging (MRI) data. However, the efficacies of dif...
We present an approach for automatic diagnosis of tissue biopsies. Our methodology consists of a quantitative phase imaging tissue scanner and machine learning algorithms to process these data. We illustrate the performance by automatic Gleason gradi...
RATIONALE: Timely detection of pseudoprogression (PSP) is crucial for the management of patients with high-grade glioma (HGG) but remains difficult. Textural features of O-(2-[18F]fluoroethyl)-L-tyrosine positron emission tomography (FET-PET) mirror ...