Pathology

Human-level COVID-19 diagnosis from low-dose CT scans using a two-stage time-distributed capsule network.

Reverse transcription-polymerase chain reaction is currently the gold standard in COVID-19 diagnosis. It can, however, take days to provide the diagnosis, and false negative rate is relatively high. Imaging, in particular chest computed tomography (CT), can assist with diagnosis and assessment of this disease. Nevertheless, it is shown that standard dose CT scan gives significant radiation burden ...

Unsupervised machine learning for identifying important visual features through bag-of-words using histopathology data from chronic kidney disease.

Pathologists use visual classification to assess patient kidney biopsy samples when diagnosing the underlying cause of kidney disease. However, the assessment is qualitative, or semi-quantitative at best, and reproducibility is challenging. To discover previously unknown features which predict patient outcomes and overcome substantial interobserver variability, we developed an unsupervised bag-of-...

Robotic biliary surgery for benign and malignant bile duct obstruction: a case series.

The majority of patients with benign or malignant biliary obstruction require surgical treatment with a bilio-enteric anastomosis. This requires fine ...

Evaluation of Nano-curcumin effects against Tartrazine-induced abnormalities in liver and kidney histology and other biochemical parameters.

In the current study, 40 albino male rats were investigated to evaluate the impact of Nano-curcumin (Nano-CUR) administration against Tartrazine (TZ)-...

Semisolid Pharmaceutical Product Characterization Using Non-invasive X-ray Microscopy and AI-Based Image Analytics.

This work reports the use of X-ray microscopy (XRM) imaging to characterize the microstructure of semisolid formulations containing multiple immiscibl...

Deep learning-enabled assessment of cardiac allograft rejection from endomyocardial biopsies.

Endomyocardial biopsy (EMB) screening represents the standard of care for detecting allograft rejections after heart transplant. Manual interpretation...

Improved-Mask R-CNN: Towards an accurate generic MSK MRI instance segmentation platform (data from the Osteoarthritis Initiative).

INTRODUCTION: Objective assessment of osteoarthritis (OA) Magnetic Resonance Imaging (MRI) scans can address the limitations of the current OA assessm...

Online Diagnosis and Classification of CT Images Collected by Internet of Things Using Deep Learning.

Deep learning technology has recently played an important role in image, language processing, and feature extraction. In the past disease diagnosis, m...

Instance importance-Aware graph convolutional network for 3D medical diagnosis.

Automatic diagnosis of 3D medical data is a significant goal of intelligent healthcare. By exploiting the abundant pathological information of 3D data...

Fully automated platelet differential interference contrast image analysis via deep learning.

Platelets mediate arterial thrombosis, a leading cause of myocardial infarction and stroke. During injury, platelets adhere and spread over exposed su...

Specifying Inputs for the Computational Structure of a Surgical System via Optical Method and DLT Algorithm Based on In Vitro Experiments on Cardiovascular Tissue in Minimally Invasive and Robotic Surgery.

With the application of four optical CMOS sensors, it was possible to capture the trajectory of an endoscopic tool during an in vitro surgical experim...

Diagnosis System of Microscopic Hyperspectral Image of Hepatobiliary Tumors Based on Convolutional Neural Network.

Hepatobiliary tumor is one of the common tumors and cancers in medicine, which seriously affects people's lives, so how to accurately diagnose it is a...

Classification of breast cancer with deep learning from noisy images using wavelet transform.

In this study, breast cancer classification as benign or malignant was made using images obtained by histopathological procedures, one of the medical ...

Speeding up the Topography Imaging of Atomic Force Microscopy by Convolutional Neural Network.

Atomic force microscopy (AFM) provides unprecedented insight into surface topography research with ultrahigh spatial resolution at the subnanometer le...

Scrutinizing high-risk patients from ASC-US cytology via a deep learning model.

BACKGROUND: Atypical squamous cells of undetermined significance (ASC-US) is the most frequent but ambiguous abnormal Papanicolaou (Pap) interpretatio...

Diagnosis of Liver Cirrhosis and Liver Fibrosis by Artificial Intelligence Algorithm-Based Multislice Spiral Computed Tomography.

This research was aimed at investigating the artificial intelligence (AI) segmentation algorithm-based multislice spiral computed tomography (MSCT) in...

Radiomic and Artificial Intelligence Analysis with Textural Metrics Extracted by Contrast-Enhanced Mammography and Dynamic Contrast Magnetic Resonance Imaging to Detect Breast Malignant Lesions.

:The purpose of this study was to discriminate between benign and malignant breast lesions through several classifiers using, as predictors, radiomic ...

Deep contrastive learning based tissue clustering for annotation-free histopathology image analysis.

BACKGROUND: Deep convolutional neural networks (CNNs) have yielded promising results in automatic whole slide images (WSIs) processing for digital pat...

High Resolution of Plasmonic Resonance Scattering Imaging with Deep Learning.

The dark-field microscopy (DFM) imaging technology has the advantage of a high signal-to-noise ratio, and it is often used for real-time monitoring of...

Computational pathology for musculoskeletal conditions using machine learning: advances, trends, and challenges.

Histopathology is widely used to analyze clinical biopsy specimens and tissues from pre-clinical models of a variety of musculoskeletal conditions. Hi...