Laboratory investigation; a journal of technical methods and pathology
Aug 22, 2020
Radiomics has potential advantages in the noninvasive histopathological and molecular diagnosis of gliomas. We aimed to develop a novel image signature (IS)-based radiomics model to achieve multilayered preoperative diagnosis and prognostic stratific...
The application of deep learning for automated segmentation (delineation of boundaries) of histologic primitives (structures) from whole slide images can facilitate the establishment of novel protocols for kidney biopsy assessment. Here, we developed...
RATIONALE AND OBJECTIVES: A more accurate lung nodule detection algorithm is needed. We developed a modified three-dimensional (3D) U-net deep-learning model for the automated detection of lung nodules on chest CT images. The purpose of this study wa...
Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine
Aug 21, 2020
PURPOSE: MRI of endolymphatic hydrops (EH) 4 h after intravenous administration of a single dose of gadolinium-based contrast agent is used for clinical examination in some institutions; however, further improvement in image quality would be valuable...
For a long time, expressions have been something that human beings are proud of. That is an essential difference between us and machines. With the development of computers, we are more eager to develop communication between humans and machines, espec...
BACKGROUND: Compartmental models dominate epidemic modeling. Transmission parameters between compartments are typically estimated through stochastic parameterization processes that depends on detailed statistics of transmission characteristics, which...
Translational vision science & technology
Aug 21, 2020
PURPOSE: To present a fully automatic method to estimate the corneal endothelium parameters from specular microscopy images and to use it to study a one-year follow-up after ultrathin Descemet stripping automated endothelial keratoplasty.
OBJECTIVES: We survey recent developments in medical Information Extraction (IE) as reported in the literature from the past three years. Our focus is on the fundamental methodological paradigm shift from standard Machine Learning (ML) techniques to ...
INTRODUCTION: There has been a rapid development of deep learning (DL) models for medical imaging. However, DL requires a large labeled dataset for training the models. Getting large-scale labeled data remains a challenge, and multi-center datasets s...
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