Pathology

A Deep-Learning-Computed Cancer Score for the Identification of Human Hepatocellular Carcinoma Area Based on a Six-Colour Multiplex Immunofluorescence Panel.

Liver cancer is one of the most frequently diagnosed and fatal cancers worldwide, with hepatocellular carcinoma (HCC) being the most common primary liver cancer. Hundreds of studies involving thousands of patients have now been analysed across different cancer types, including HCC, regarding the effects of immune infiltrates on the prognosis of cancer patients. However, for these analyses, an unam...

Mine local homogeneous representation by interaction information clustering with unsupervised learning in histopathology images.

BACKGROUND AND OBJECTIVE: The success of data-driven deep learning for histopathology images often depends on high-quality training sets and fine-grained annotations. However, as tumors are heterogeneous and annotations are expensive, unsupervised learning approaches are desirable to obtain full automation.

Success rates and outcomes of the robotic NICE procedure across complicated and uncomplicated diverticulitis cases.

INTRODUCTION: We implemented the NICE procedure as a robotic natural orifice colorectal resection utilizing the rectum to extract the specimen and com...

Synthesis of large scale 3D microscopic images of 3D cell cultures for training and benchmarking.

The analysis of 3D microscopic cell culture images plays a vital role in the development of new therapeutics. While 3D cell cultures offer a greater s...

Artificial intelligence velocimetry reveals in vivo flow rates, pressure gradients, and shear stresses in murine perivascular flows.

Quantifying the flow of cerebrospinal fluid (CSF) is crucial for understanding brain waste clearance and nutrient delivery, as well as edema in pathol...

A Novel Deep-Learning-Based CADx Architecture for Classification of Thyroid Nodules Using Ultrasound Images.

Nodules of thyroid cancer occur in the cells of the thyroid as benign or malign types. Thyroid sonographic images are mostly used for diagnosis of thy...

Machine-learning-powered extraction of molecular diffusivity from single-molecule images for super-resolution mapping.

While critical to biological processes, molecular diffusion is difficult to quantify, and spatial mapping of local diffusivity is even more challengin...

Deep learning-based segmentation and quantification of podocyte foot process morphology suggests differential patterns of foot process effacement across kidney pathologies.

Morphological alterations at the kidney filtration barrier increase intrinsic capillary wall permeability resulting in albuminuria. However, automated...

Simultaneous excision of pelvic lipoma and robot-assisted radical prostatectomy.

Lipoma is a benign mesenchymal tumour that can develop in any part of the body containing adipose tissue. Very few cases of pelvic lipomas have been r...

Deep learning-enabled segmentation of ambiguous bioimages with deepflash2.

Bioimages frequently exhibit low signal-to-noise ratios due to experimental conditions, specimen characteristics, and imaging trade-offs. Reliable seg...

Deep learning neural network image analysis of immunohistochemical protein expression reveals a significantly reduced expression of biglycan in breast cancer.

New breast cancer biomarkers have been sought for better tumor characterization and treatment. Among these putative markers, there is Biglycan (BGN). ...

Investigation of radiomics and deep convolutional neural networks approaches for glioma grading.

To determine glioma grading by applying radiomic analysis or deep convolutional neural networks (DCNN) and to benchmark both approaches on broader val...

Breast Tumor Classification using Short-ResNet with Pixel-based Tumor Probability Map in Ultrasound Images.

Breast cancer is the most common form of cancer and is still the second leading cause of death for women in the world. Early detection and treatment o...

The value of artificial intelligence in the diagnosis of lung cancer: A systematic review and meta-analysis.

Lung cancer is a common malignant tumor disease with high clinical disability and death rates. Currently, lung cancer diagnosis mainly relies on manua...

Multi CNN based automatic detection of mitotic nuclei in breast histopathological images.

In breast cancer diagnosis, the number of mitotic cells in a specific area is an important measure. It indicates how far the tumour has spread, which ...

Generalizable biomarker prediction from cancer pathology slides with self-supervised deep learning: A retrospective multi-centric study.

Deep learning (DL) can predict microsatellite instability (MSI) from routine histopathology slides of colorectal cancer (CRC). However, it is unclear ...

Tile-based microscopic image processing for malaria screening using a deep learning approach.

BACKGROUND: Manual microscopic examination remains the golden standard for malaria diagnosis. But it is laborious, and pathologists with experience ar...

AMLnet, A deep-learning pipeline for the differential diagnosis of acute myeloid leukemia from bone marrow smears.

Acute myeloid leukemia (AML) is a deadly hematological malignancy. Cellular morphology detection of bone marrow smears based on the French-American-Br...

Incidence and Predicting Factors of Histopathological Features at Robot-Assisted Radical Prostatectomy in the mpMRI Era: Results of a Single Tertiary Referral Center.

: To describe the predictors of cribriform variant status and perineural invasion (PNI) in robot-assisted radical prostatectomy (RARP) histology. To d...

Can artificial intelligence accelerate the diagnosis of inherited retinal diseases? Protocol for a data-only retrospective cohort study (Eye2Gene).

INTRODUCTION: Inherited retinal diseases (IRD) are a leading cause of visual impairment and blindness in the working age population. Mutations in over...