Pathology

Generic Isolated Cell Image Generator.

Building automated cancer screening systems based on image analysis is currently a hot topic in computer vision and medical imaging community. One of the biggest challenges of such systems, especially those using state-of-the-art deep learning techniques, is that they usually require a large amount of training data to be accurate. However, in the medical field, the confidentiality of the data and ...

Applications of Computer Modeling and Simulation in Cartilage Tissue Engineering.

BACKGROUND: Advances in cartilage tissue engineering have demonstrated noteworthy potential for developing cartilage for implantation onto sites impacted by joint degeneration and injury. To supplement resource-intensive in vivo and in vitro studies required for cartilage tissue engineering, computational models and simulations can assist in enhancing experimental design.

ARA: accurate, reliable and active histopathological image classification framework with Bayesian deep learning.

Machine learning algorithms hold the promise to effectively automate the analysis of histopathological images that are routinely generated in clinical...

Assessment of Accuracy of an Artificial Intelligence Algorithm to Detect Melanoma in Images of Skin Lesions.

IMPORTANCE: A high proportion of suspicious pigmented skin lesions referred for investigation are benign. Techniques to improve the accuracy of melano...

Computer-Aided Diagnosis in Histopathological Images of the Endometrium Using a Convolutional Neural Network and Attention Mechanisms.

Uterine cancer (also known as endometrial cancer) can seriously affect the female reproductive system, and histopathological image analysis is the gol...

Microphysiological sensing platform for an in-situ detection of tissue-secreted cytokines.

Understanding the protein-secretion dynamics from single, specific tissues is critical toward the advancement of disease detection and treatments. How...

Deep Learning-Based Gleason Grading of Prostate Cancer From Histopathology Images-Role of Multiscale Decision Aggregation and Data Augmentation.

Visual inspection of histopathology images of stained biopsy tissue by expert pathologists is the standard method for grading of prostate cancer (PCa)...

A new approach for brain tumor diagnosis system: Single image super resolution based maximum fuzzy entropy segmentation and convolutional neural network.

Magnetic resonance imaging (MRI) images can be used to diagnose brain tumors. Thanks to these images, some methods have so far been proposed in order ...

Neural network methodology for real-time modelling of bio-heat transfer during thermo-therapeutic applications.

Real-time simulation of bio-heat transfer can improve surgical feedback in thermo-therapeutic treatment, leading to technical innovations to surgical ...

Automated diagnosis of heart valve degradation using novelty detection algorithms and machine learning.

The blood flow through the major vessels holds great diagnostic potential for the identification of cardiovascular complications and is therefore rout...

Radiologic-Radiomic Machine Learning Models for Differentiation of Benign and Malignant Solid Renal Masses: Comparison With Expert-Level Radiologists.

The objective of our study was to compare the performance of radiologicradiomic machine learning (ML) models and expert-level radiologists for differ...

Diagnosis and classification of pediatric acute appendicitis by artificial intelligence methods: An investigator-independent approach.

Acute appendicitis is one of the major causes for emergency surgery in childhood and adolescence. Appendectomy is still the therapy of choice, but con...

Sequential Saliency Guided Deep Neural Network for Joint Mitosis Identification and Localization in Time-Lapse Phase Contrast Microscopy Images.

The analysis of cell mitotic behavior plays important role in many biomedical research and medical diagnostic applications. To improve the accuracy of...

Detection of Lung Cancer Lymph Node Metastases from Whole-Slide Histopathologic Images Using a Two-Step Deep Learning Approach.

The application of deep learning for the detection of lymph node metastases on histologic slides has attracted worldwide attention due to its potentia...

Hover-Net: Simultaneous segmentation and classification of nuclei in multi-tissue histology images.

Nuclear segmentation and classification within Haematoxylin & Eosin stained histology images is a fundamental prerequisite in the digital pathology wo...

Independent validation of machine learning in diagnosing breast Cancer on magnetic resonance imaging within a single institution.

BACKGROUND: As artificial intelligence methods for the diagnosis of disease advance, we aimed to evaluate machine learning in the predictive task of d...

Pre and post-hoc diagnosis and interpretation of malignancy from breast DCE-MRI.

We propose a new method for breast cancer screening from DCE-MRI based on a post-hoc approach that is trained using weakly annotated data (i.e., label...

Neuromuscular actuation of biohybrid motile bots.

The integration of muscle cells with soft robotics in recent years has led to the development of biohybrid machines capable of untethered locomotion. ...

Towards pixel-to-pixel deep nucleus detection in microscopy images.

BACKGROUND: Nucleus is a fundamental task in microscopy image analysis and supports many other quantitative studies such as object counting, segmentat...

Technical considerations of multi-parametric tissue outcome prediction methods in acute ischemic stroke patients.

Decisions regarding acute stroke treatment rely heavily on imaging, but interpretation can be difficult for physicians. Machine learning methods can a...