Pathology

Phenotypic Antimicrobial Susceptibility Testing with Deep Learning Video Microscopy.

Timely determination of antimicrobial susceptibility for a bacterial infection enables precision prescription, shortens treatment time, and helps minimize the spread of antibiotic resistant infections. Current antimicrobial susceptibility testing (AST) methods often take several days and thus impede these clinical and health benefits. Here, we present an AST method by imaging freely moving bacteri...

Glucagonoma and Glucagonoma Syndrome: One Center's Experience of Six Cases.

Glucagonoma is an extremely rare neuroendocrine tumor arising from pancreatic islet cells. Although patients with glucagonoma manifest multiple typical symptoms, early diagnosis remains difficult due to the scarcity of this disease. In this study, we retrospectively screened the database of the pancreas center of Nanjing Medical University. A total of six cases diagnosed as glucagonoma during th...

Semantic segmentation of mFISH images using convolutional networks.

Multicolor in situ hybridization (mFISH) is a karyotyping technique used to detect major chromosomal alterations using fluorescent probes and imaging ...

Automated classification of celiac disease during upper endoscopy: Status quo and quo vadis.

A large amount of digital image material is routinely captured during esophagogastroduodenoscopies but, for the most part, is not used for confirming ...

Automated pixel-wise brain tissue segmentation of diffusion-weighted images via machine learning.

The diffusion-weighted (DW) MR signal sampled over a wide range of b-values potentially allows for tissue differentiation in terms of cellularity, mic...

MuDeRN: Multi-category classification of breast histopathological image using deep residual networks.

MOTIVATION: Identifying carcinoma subtype can help to select appropriate treatment options and determining the subtype of benign lesions can be benefi...

An improved deep learning approach for detection of thyroid papillary cancer in ultrasound images.

Unlike daily routine images, ultrasound images are usually monochrome and low-resolution. In ultrasound images, the cancer regions are usually blurred...

Assessing Breast Cancer Risk with an Artificial Neural Network.

Objectives: Radiologists face uncertainty in making decisions based on their judgment of breast cancer risk. Artificial intelligence and machine learn...

Ultrasonographic Reference Values of Kidney Dimensions and Clinicopathological Findings Associating the Transcutaneous Ultrasound-Guided Renal Biopsy in Donkeys (Equus asinus).

This study aimed to establish normal ultrasonographic reference values of kidney dimensions in donkeys (Equus asinus) and to describe and evaluate the...

Absolute cosine-based SVM-RFE feature selection method for prostate histopathological grading.

OBJECTIVE: Feature selection (FS) methods are widely used in grading and diagnosing prostate histopathological images. In this context, FS is based on...

Computer-aided diagnosis of lung nodule using gradient tree boosting and Bayesian optimization.

We aimed to evaluate a computer-aided diagnosis (CADx) system for lung nodule classification focussing on (i) usefulness of the conventional CADx syst...

Deep Convolutional Hashing for Low-Dimensional Binary Embedding of Histopathological Images.

Compact binary representations of histopa-thology images using hashing methods provide efficient approximate nearest neighbor search for direct visual...

Deep learning massively accelerates super-resolution localization microscopy.

The speed of super-resolution microscopy methods based on single-molecule localization, for example, PALM and STORM, is limited by the need to record ...

Inferring Clinical Correlations from EEG Reports with Deep Neural Learning.

Successful diagnosis and management of neurological dysfunction relies on proper communication between the neurologist and the primary physician (or o...

A Multi-scale U-Net for Semantic Segmentation of Histological Images from Radical Prostatectomies.

Gleason grading of histological images is important in risk assessment and treatment planning for prostate cancer patients. Much research has been don...

Identifying tumor in pancreatic neuroendocrine neoplasms from Ki67 images using transfer learning.

The World Health Organization (WHO) has clear guidelines regarding the use of Ki67 index in defining the proliferative rate and assigning grade for pa...

Prevalence and genotypes of Giardia lamblia from stray dogs and cats in Guangdong, China.

Giardia lamblia is a worldwide zoonotic intestinal parasite that infects humans and a wide range of mammals including dogs and cats, causing giardiasi...

A deep-learning classifier identifies patients with clinical heart failure using whole-slide images of H&E tissue.

Over 26 million people worldwide suffer from heart failure annually. When the cause of heart failure cannot be identified, endomyocardial biopsy (EMB)...

Identification of Three Rheumatoid Arthritis Disease Subtypes by Machine Learning Integration of Synovial Histologic Features and RNA Sequencing Data.

OBJECTIVE: In this study, we sought to refine histologic scoring of rheumatoid arthritis (RA) synovial tissue by training with gene expression data an...

Bioactive polymeric formulations for wound healing.

Ricinoleic acid (RA) has potential to promote wound healing because of its analgesic and anti-inflammatory properties. This study investigates the syn...