OBJECTIVE: To compare the CT texture feature reproducibility of 2D and 3D segmentations and their machine learning (ML)-based classifications for predicting human papilloma virus (HPV) status in oropharyngeal squamous cell carcinoma (OPSCC).
BACKGROUND: The RENAL (radius [R], exophytic/endophytic [E], nearness to collecting system/sinus [N], anterior/posterior [A], and location relative to polar lines [L]) and the PADUA (preoperative aspects and dimensions used for an anatomical classifi...
Supervised training of deep learning models requires large labeled datasets. There is a growing interest in obtaining such datasets for medical image analysis applications. However, the impact of label noise has not received sufficient attention. Rec...
Virchows Archiv : an international journal of pathology
Jun 15, 2020
The International Society of Urological Pathology (ISUP) hosts a reference image database supervised by experts with the purpose of establishing an international standard in prostate cancer grading. Here, we aimed to identify areas of grading difficu...
Acta radiologica (Stockholm, Sweden : 1987)
Jun 9, 2020
BACKGROUND: Good feature reproducibility enhances model reliability. The manual segmentation of gastric cancer with liver metastasis (GCLM) can be time-consuming and unstable.
Laboratory investigation; a journal of technical methods and pathology
May 29, 2020
A pathological evaluation is one of the most important methods for the diagnosis of malignant lymphoma. A standardized diagnosis is occasionally difficult to achieve even by experienced hematopathologists. Therefore, established procedures including ...
AJNR. American journal of neuroradiology
May 21, 2020
BACKGROUND AND PURPOSE: Fast and accurate quantification of globe volumes in the event of an ocular trauma can provide clinicians with valuable diagnostic information. In this work, an automated workflow using a deep learning-based convolutional neur...
Journal of vascular and interventional radiology : JVIR
May 4, 2020
PURPOSE: To develop and validate a deep learning model based on routine magnetic resonance (MR) imaging obtained before uterine fibroid embolization to predict procedure outcome.
Expert review of molecular diagnostics
May 3, 2020
BACKGROUND: A key objective in glaucoma is to identify those at risk of rapid progression and blindness. Recently, a novel first-in-man method for visualising apoptotic retinal cells called DARC (Detection-of-Apoptosing-Retinal-Cells) was reported. T...
European journal of nuclear medicine and molecular imaging
Apr 20, 2020
PURPOSE: In selective internal radiation therapy (SIRT), an accurate total liver segmentation is required for activity prescription and absorbed dose calculation. Our goal was to investigate the feasibility of using automatic liver segmentation based...