Pathology

An efficient deep equilibrium model for medical image segmentation.

In this paper, we propose an effective method that takes the advantages of classical methods and deep learning technology for medical image segmentation through modeling the neural network as a fixed point iteration seeking for system equilibrium by adding a feedback loop. In particular, the nuclear segmentation of medical image is used as an example to demonstrate the proposed method where it can...

Fast intraoperative histology-based diagnosis of gliomas with third harmonic generation microscopy and deep learning.

Management of gliomas requires an invasive treatment strategy, including extensive surgical resection. The objective of the neurosurgeon is to maximize tumor removal while preserving healthy brain tissue. However, the lack of a clear tumor boundary hampers the neurosurgeon's ability to accurately detect and resect infiltrating tumor tissue. Nonlinear multiphoton microscopy, in particular higher ha...

Classification of multi-differentiated liver cancer pathological images based on deep learning attention mechanism.

PURPOSE: Liver cancer is one of the most common malignant tumors in the world, ranking fifth in malignant tumors. The degree of differentiation can re...

Intelligent Fault Diagnosis for Chemical Processes Using Deep Learning Multimodel Fusion.

Deep learning technology has been widely used in fault diagnosis for chemical processes. However, most deep learning technologies currently adopted on...

Breast Cancer Detection and Classification Empowered With Transfer Learning.

Cancer is a major public health issue in the modern world. Breast cancer is a type of cancer that starts in the breast and spreads to other parts of t...

SONNET: A Self-Guided Ordinal Regression Neural Network for Segmentation and Classification of Nuclei in Large-Scale Multi-Tissue Histology Images.

Automated nuclei segmentation and classification are the keys to analyze and understand the cellular characteristics and functionality, supporting com...

A Convolutional Neural Network and Graph Convolutional Network Based Framework for Classification of Breast Histopathological Images.

The spatial correlation among different tissue components is an essential characteristic for diagnosis of breast cancers based on histopathological im...

Privacy-Preserving Multi-Class Support Vector Machine Model on Medical Diagnosis.

With the rapid development of machine learning in the medical cloud system, cloud-assisted medical computing provides a concrete platform for remote r...

Diagnosis of Brain Tumor Using Light Weight Deep Learning Model with Fine-Tuning Approach.

Brain cancer is a rare and deadly disease with a slim chance of survival. One of the most important tasks for neurologists and radiologists is to dete...

Detection of mitotic HEp-2 cell images: role of feature representation and classification framework under class skew.

We propose and analyze a framework to detect and identify the mitotic type staining patterns among different non-mitotic (interphase) patterns on HEp-...

Spectral organ fingerprints for machine learning-based intraoperative tissue classification with hyperspectral imaging in a porcine model.

Visual discrimination of tissue during surgery can be challenging since different tissues appear similar to the human eye. Hyperspectral imaging (HSI)...

Research on Sports Health Care Information System Based on Computer Deep Learning Algorithm.

There are various problems in diagnosing and treating tumor diseases in significant hospitals. The content includes misjudgement and over-surgery issu...

Intelligent sort-timing prediction for image-activated cell sorting.

Intelligent image-activated cell sorting (iIACS) has enabled high-throughput image-based sorting of single cells with artificial intelligence (AI) alg...

Intelligent temperature modeling in robotic cortical bone milling process based on teaching-learning-based optimization algorithm.

Bone milling is one of the most important and sensitive biomechanical processes in the field of medical engineering. This process is used in orthopedi...

HunCRC: annotated pathological slides to enhance deep learning applications in colorectal cancer screening.

Histopathology is the gold standard method for staging and grading human tumors and provides critical information for the oncoteam's decision making. ...

Biomedical Microscopic Imaging in Computational Intelligence Using Deep Learning Ensemble Convolution Learning-Based Feature Extraction and Classification.

Microscopy image analysis gives quantitative support for enhancing the characterizations of various diseases, including breast cancer, lung cancer, an...

Transition from da Vinci to Versius robotic surgical system: initial experience and outcomes of over 100 consecutive procedures.

We sought to describe the development of the robotic urology program at Sindh Institute of Urology and Transplantation (SIUT) and the feasibility of t...

Robotic Pancreatoduodenectomy for Pancreatic Head Cancer: a Case Report of a Standardized Technique.

Robotic pancreatoduodenectomy (RPD) for pancreatic cancer is a challenging procedure. Aberrant vasculature may increase the technical difficulty. Seve...

DARC: Deep adaptive regularized clustering for histopathological image classification.

In recent years, deep learning as a state-of-the-art machine learning technique has made great success in histopathological image classification. Howe...

MVFStain: Multiple virtual functional stain histopathology images generation based on specific domain mapping.

To the best of our knowledge, artificial intelligence stain generation is an urgent requirement for histopathology images. Pathological examinations u...