Pathology

Piloting a Deep Learning Model for Predicting Nuclear BAP1 Immunohistochemical Expression of Uveal Melanoma from Hematoxylin-and-Eosin Sections.

BACKGROUND: Uveal melanoma (UM) is the most common primary intraocular malignancy in adults. Monosomy 3 and mutation are strong prognostic factors predicting metastatic risk in UM. Nuclear BAP1 (nBAP1) expression is a close immunohistochemical surrogate for both genetic alterations. Not all laboratories perform routine BAP1 immunohistochemistry or genetic testing, and rely mainly on clinical info...

Estimation of Ultrasound Echogenicity Map from B-Mode Images Using Convolutional Neural Network.

In ultrasound B-mode imaging, speckle noises decrease the accuracy of estimation of tissue echogenicity of imaged targets from the amplitude of the echo signals. In addition, since the granular size of the speckle pattern is affected by the point spread function (PSF) of the imaging system, the resolution of B-mode image remains limited, and the boundaries of tissue structures often become blurred...

Application of artificial intelligence using a novel EUS-based convolutional neural network model to identify and distinguish benign and malignant hepatic masses.

BACKGROUND AND AIMS: Detection and characterization of focal liver lesions (FLLs) is key for optimizing treatment for patients who may have a primary ...

Clinically applicable histopathological diagnosis system for gastric cancer detection using deep learning.

The early detection and accurate histopathological diagnosis of gastric cancer increase the chances of successful treatment. The worldwide shortage of...

Preliminary clinical assessment of dynamic carbon-11 methionine positron-emission tomography/computed tomography for the diagnosis of the pathologies in patients with musculoskeletal lesions: a prospective study.

BACKGROUND: This study prospectively assessed the diagnostic capacity of dynamic carbon-11 methionine (C-11 MET) positron-emission tomography (PET)/co...

Artificial Intelligence-Based Quantification of Epithelial Proliferation in Mammary Glands of Rats and Oviducts of Göttingen Minipigs.

Quantitative assessment of proliferation can be an important endpoint in toxicologic pathology. Traditionally, cell proliferation is quantified by lab...

[Robot-controlled MRI-guided transrectal prostate biopsy, a promising technique].

At the so-called in-bore, MRI-guided prostate biopsy, the radiologist in the MRI suite manually directs a rectal biopsy needle guide at an abnormality...

----Evaluation of Design and Fabrication of Food-Grade Nanofibers from Chitosan-Gelatin for Nanoencapsulation of Stigmasterol Using the Electrospinning Method.

In this research, electrospinning method was employed to fabricate food-grade nanofibers (NFs) from chitosan-gelatin combination for stigmasterol enc...

Objective assessment of stored blood quality by deep learning.

Stored red blood cells (RBCs) are needed for life-saving blood transfusions, but they undergo continuous degradation. RBC storage lesions are often as...

A novel image signature-based radiomics method to achieve precise diagnosis and prognostic stratification of gliomas.

Radiomics has potential advantages in the noninvasive histopathological and molecular diagnosis of gliomas. We aimed to develop a novel image signatur...

Development and evaluation of deep learning-based segmentation of histologic structures in the kidney cortex with multiple histologic stains.

The application of deep learning for automated segmentation (delineation of boundaries) of histologic primitives (structures) from whole slide images ...

Spectral-Spatial Features Integrated Convolution Neural Network for Breast Cancer Classification.

Cancer identification and classification from histopathological images of the breast depends greatly on experts, and computer-aided diagnosis can play...

β-hydroxy-β-methylbutyrate supplementation benefits the effects of resistance training on body fat reduction via increased irisin expression in white adipose tissue.

The effects of resistance training (RT) associated with calcium β-hydroxyβ-methylbutyrate (CaHMB) supplementation on the body composition and gene exp...

Deep Learning for Assessing the Corneal Endothelium from Specular Microscopy Images up to 1 Year after Ultrathin-DSAEK Surgery.

PURPOSE: To present a fully automatic method to estimate the corneal endothelium parameters from specular microscopy images and to use it to study a o...

High tissue contrast image synthesis via multistage attention-GAN: Application to segmenting brain MR scans.

Magnetic resonance imaging (MRI) presents a detailed image of the internal organs via a magnetic field. Given MRI's non-invasive advantage in repeated...

Application of Artificial Neural Networks for Accurate Determination of the Complex Permittivity of Biological Tissue.

Medical devices making use of radio frequency (RF) and microwave (MW) fields have been studied as alternatives to existing diagnostic and therapeutic ...

Using Deep Learning with Convolutional Neural Network Approach to Identify the Invasion Depth of Endometrial Cancer in Myometrium Using MR Images: A Pilot Study.

Myometrial invasion affects the prognosis of endometrial cancer. However, discrepancies exist between pre-operative magnetic resonance imaging staging...

Deep computational pathology in breast cancer.

Deep Learning (DL) algorithms are a set of techniques that exploit large and/or complex real-world datasets for cross-domain and cross-discipline pred...

Artificial intelligence-assisted cytology for detection of cervical intraepithelial neoplasia or invasive cancer: A multicenter, clinical-based, observational study.

OBJECTIVE: Artificial intelligence (AI) could automatedly detect abnormalities in digital cytological images, however, the effect in cervical cancer s...

Deep learning method for localization and segmentation of abdominal CT.

Computed Tomography (CT) imaging is widely used for studying body composition, i.e., the proportion of muscle and fat tissues with applications in are...