Pathology

Clinical characteristics and oncological outcomes in negative multiparametric MRI patients undergoing robot-assisted radical prostatectomy.

BACKGROUND: Efforts are ongoing to try and find ways to reduce the number of unnecessary prostate biopsies without missing clinically significant prostate cancers (csPCa). The utility of multiparametric magnetic resonance imaging (mpMRI) in detecting prostate cancer (PCa) shows promise to be used as triage test for systematic prostate biopsy. Our aim is to Study clinical parameters and oncological...

Neural networks for increased accuracy of allergenic pollen monitoring.

Monitoring of airborne pollen concentrations provides an important source of information for the globally increasing number of hay fever patients. Airborne pollen is traditionally counted under the microscope, but with the latest developments in image recognition methods, automating this process has become feasible. A challenge that persists, however, is that many pollen grains cannot be distingui...

LiverNet: efficient and robust deep learning model for automatic diagnosis of sub-types of liver hepatocellular carcinoma cancer from H&E stained liver histopathology images.

PURPOSE: Liver cancer is one of the most common types of cancers in Asia with a high mortality rate. A common method for liver cancer diagnosis is the...

A survey on applications of deep learning in microscopy image analysis.

Advanced microscopy enables us to acquire quantities of time-lapse images to visualize the dynamic characteristics of tissues, cells or molecules. Mic...

SPASOS 1.1: a program for the inference of ancestral shape ontogenies.

We recently published a method to infer ancestral landmark-based shape ontogenies that takes into account the possible existence of changes in develop...

Prediction of the motion of chest internal points using a recurrent neural network trained with real-time recurrent learning for latency compensation in lung cancer radiotherapy.

During the radiotherapy treatment of patients with lung cancer, the radiation delivered to healthy tissue around the tumor needs to be minimized, whic...

Cartilage structure increases swimming efficiency of underwater robots.

Underwater robots are useful for exploring valuable resources and marine life. Traditional underwater robots use screw propellers, which may be harmfu...

A deep learning algorithm for 3D cell detection in whole mouse brain image datasets.

Understanding the function of the nervous system necessitates mapping the spatial distributions of its constituent cells defined by function, anatomy ...

Resection of Intracranial Tumors with a Robotic-Assisted Digital Microscope: A Preliminary Experience with Robotic Scope.

BACKGROUND: Magnified intraoperative visualization is of paramount importance during microsurgical procedures. Although the introduction of the operat...

Cell morphology-based machine learning models for human cell state classification.

Herein, we implement and access machine learning architectures to ascertain models that differentiate healthy from apoptotic cells using exclusively f...

Ischemic stroke-induced polyaxonal innervation at the neuromuscular junction is attenuated by robot-assisted mechanical therapy.

Ischemic stroke is a leading cause of disability world-wide. Mounting evidence supports neuromuscular pathology following stroke, yet mechanisms of dy...

Translational Applications of Artificial Intelligence and Machine Learning for Diagnostic Pathology in Lymphoid Neoplasms: A Comprehensive and Evolutive Analysis.

Genomic analysis and digitalization of medical records have led to a big data scenario within hematopathology. Artificial intelligence and machine lea...

Spatially Constrained Context-Aware Hierarchical Deep Correlation Filters for Nucleus Detection in Histology Images.

Nucleus detection in histology images is a fundamental step for cellular-level analysis in computational pathology. In clinical practice, quantitative...

Using deep learning convolutional neural networks to automatically perform cerebral aqueduct CSF flow analysis.

Since the development of phase-contrast magnetic resonance imaging (PC-MRI), quantification of cerebrospinal fluid (CSF) flow across the cerebral aque...

Deep-Learning-Driven Quantification of Interstitial Fibrosis in Digitized Kidney Biopsies.

Interstitial fibrosis and tubular atrophy (IFTA) on a renal biopsy are strong indicators of disease chronicity and prognosis. Techniques that are typi...

Effects of a Differential Diagnosis List of Artificial Intelligence on Differential Diagnoses by Physicians: An Exploratory Analysis of Data from a Randomized Controlled Study.

A diagnostic decision support system (DDSS) is expected to reduce diagnostic errors. However, its effect on physicians' diagnostic decisions remains u...

Clinical value of radiomics and machine learning in breast ultrasound: a multicenter study for differential diagnosis of benign and malignant lesions.

OBJECTIVES: We aimed to assess the performance of radiomics and machine learning (ML) for classification of non-cystic benign and malignant breast les...

Artificial intelligence for advance requesting of immunohistochemistry in diagnostically uncertain prostate biopsies.

The use of immunohistochemistry in the reporting of prostate biopsies is an important adjunct when the diagnosis is not definite on haematoxylin and e...

Experimental evaluation of deep learning method in reticulocyte enumeration in peripheral blood.

INTRODUCTION: Reticulocytes (RET) are immature red blood cells, and RET enumeration in peripheral blood has important clinical value in diagnosis, tre...

Deep Learning in Biomedical Optics.

This article reviews deep learning applications in biomedical optics with a particular emphasis on image formation. The review is organized by imaging...