Pathology

A low-cost, automated parasite diagnostic system via a portable, robotic microscope and deep learning.

Manual hand counting of parasites in fecal samples requires costly components and substantial expertise, limiting its use in resource-constrained settings and encouraging overuse of prophylactic medication. To address this issue, a cost-effective, automated parasite diagnostic system that does not require special sample preparation or a trained user was developed. It is composed of an inexpensive ...

Spatio-temporal deep learning models for tip force estimation during needle insertion.

PURPOSE: Precise placement of needles is a challenge in a number of clinical applications such as brachytherapy or biopsy. Forces acting at the needle cause tissue deformation and needle deflection which in turn may lead to misplacement or injury. Hence, a number of approaches to estimate the forces at the needle have been proposed. Yet, integrating sensors into the needle tip is challenging and a...

Automated segmentation of cell membranes to evaluate HER2 status in whole slide images using a modified deep learning network.

The uncontrollable growth of cells in the breast tissue causes breast cancer which is the second most common type of cancer affecting women in the Uni...

Ultrasound prostate segmentation based on multidirectional deeply supervised V-Net.

PURPOSE: Transrectal ultrasound (TRUS) is a versatile and real-time imaging modality that is commonly used in image-guided prostate cancer interventio...

Deep transfer learning methods for colon cancer classification in confocal laser microscopy images.

PURPOSE: The gold standard for colorectal cancer metastases detection in the peritoneum is histological evaluation of a removed tissue sample. For fee...

Diagnosis of cervical squamous cell carcinoma and cervical adenocarcinoma based on Raman spectroscopy and support vector machine.

In this report, we collected the Raman spectrum of cervical adenocarcinoma and cervical squamous cell carcinoma tissues by a micro-Raman spectroscopy ...

Use of Magnetic Resonance Imaging and Artificial Intelligence in Studies of Diagnosis of Parkinson's Disease.

Parkinson's disease (PD) is a common neurodegenerative disorder. It has a delitescent onset and a slow progress. The clinical manifestations of PD in ...

Pathologist-level classification of histopathological melanoma images with deep neural networks.

BACKGROUND: The diagnosis of most cancers is made by a board-certified pathologist based on a tissue biopsy under the microscope. Recent research reve...

Automated Classification of Apoptosis in Phase Contrast Microscopy Using Capsule Network.

Automatic and accurate classification of apoptosis, or programmed cell death, will facilitate cell biology research. The state-of-the-art approaches i...

A hybrid fault diagnosis methodology with support vector machine and improved particle swarm optimization for nuclear power plants.

The safety and public health during nuclear power plant operation can be enhanced by accurately recognizing and diagnosing potential problems when a m...

Does transanal total mesorectal excision of rectal cancer improve histopathology metrics and/or complication rates? A meta-analysis.

BACKGROUND: The aim of this meta-analysis was to determine whether transanal total mesorectal excision (taTME) improves histopathology metrics and/or ...

Using Artificial Intelligence to Revise ACR TI-RADS Risk Stratification of Thyroid Nodules: Diagnostic Accuracy and Utility.

Background Risk stratification systems for thyroid nodules are often complicated and affected by low specificity. Continual improvement of these syste...

Screening of disorders associated with osteosarcoma by integrated network analysis.

Osteosarcoma is a common malignant bone tumor in children and adolescents under the age of 20. However, research on the pathogenesis and treatment of ...

Adaptation of CytoProcessor for cervical cancer screening of challenging slides.

BACKGROUND: Current automated cervical cytology screening systems require purchase of a dedicated preparation machine and use of a specific staining p...

Single-cell approaches to cell competition: High-throughput imaging, machine learning and simulations.

Cell competition is a quality control mechanism in tissues that results in the elimination of less fit cells. Over the past decade, the phenomenon of ...

Cancer taxonomy: pathology beyond pathology.

The way we categorise and classify cancer types dictates not only the way we diagnose and treat patients but also many of our decisions on biomarker a...

Impact of pre-analytical variables on deep learning accuracy in histopathology.

AIMS: Machine learning (ML) binary classification in diagnostic histopathology is an area of intense investigation. Several assumptions, including tra...

Deep learning for automatic Gleason pattern classification for grade group determination of prostate biopsies.

Histopathologic grading of prostate cancer using Gleason patterns (GPs) is subject to a large inter-observer variability, which may result in suboptim...

Interpretable classification of Alzheimer's disease pathologies with a convolutional neural network pipeline.

Neuropathologists assess vast brain areas to identify diverse and subtly-differentiated morphologies. Standard semi-quantitative scoring approaches, h...

A Hybridized ELM for Automatic Micro Calcification Detection in Mammogram Images Based on Multi-Scale Features.

Detection of masses and micro calcifications are a stimulating task for radiologists in digital mammogram images. Radiologists using Computer Aided De...