Pathology

Accurate and rapid background estimation in single-molecule localization microscopy using the deep neural network BGnet.

Background fluorescence, especially when it exhibits undesired spatial features, is a primary factor...

Whole slide imaging system using deep learning-based automated focusing.

The auto focusing system, which involves moving a microscope stage along a vertical axis to find an ...

Automatic cancer tissue detection using multispectral photoacoustic imaging.

PURPOSE: In the case of multispecimen study to locate cancer regions, such as in thyroidectomy and p...

Deep learning pathological microscopic features in endemic nasopharyngeal cancer: Prognostic value and protentional role for individual induction chemotherapy.

BACKGROUND: To explore the prognostic value and the role for treatment decision of pathological micr...

Microwave tomography with phaseless data on the calcaneus by means of artificial neural networks.

The aim of this study is to use a multilayer perceptron (MLP) artificial neural network (ANN) for ph...

Automatic Identification of Breast Ultrasound Image Based on Supervised Block-Based Region Segmentation Algorithm and Features Combination Migration Deep Learning Model.

Breast cancer is a high-incidence type of cancer for women. Early diagnosis plays a crucial role in ...

Artificial intelligence in digital breast pathology: Techniques and applications.

Breast cancer is the most common cancer and second leading cause of cancer-related death worldwide. ...

Application of automated electron microscopy imaging and machine learning to characterise and quantify nanoparticle dispersion in aqueous media.

For many nanoparticle applications it is important to understand dispersion in liquids. For nanomedi...

'Emulsion locks' for the containment of hydrocarbons during surfactant flushing.

Reversible double water in oil in water (W/O/W) emulsions were developed to contain subsurface hydro...

Injection techniques for auricular nerve blocks in the rabbit cadaver.

OBJECTIVE: To describe the landmarks for localization and to determine the methodology and volume of...

Editorial on "Diagnosis of Benign and Malignant Breast Lesions on DCE-MRI by Using Radiomics and Deep Learning With Consideration of Peritumor Tissue".

Assessment of individual tumor buds using keratin immunohistochemistry: moderate interobserver agreement suggests a role for machine learning.

Tumor budding is a promising and cost-effective biomarker with strong prognostic value in colorectal...

Classification of Mammogram Images Using Multiscale all Convolutional Neural Network (MA-CNN).

Breast cancer is one of the leading causes of cancer death among women in worldwide. Early diagnosis...

Utilizing Machine Learning for Image Quality Assessment for Reflectance Confocal Microscopy.

In vivo reflectance confocal microscopy (RCM) enables clinicians to examine lesions' morphological a...

A modular cGAN classification framework: Application to colorectal tumor detection.

Automatic identification of tissue structures in the analysis of digital tissue biopsies remains an ...

Radiomics allows for detection of benign and malignant histopathology in patients with metastatic testicular germ cell tumors prior to post-chemotherapy retroperitoneal lymph node dissection.

OBJECTIVES: To evaluate whether a computed tomography (CT) radiomics-based machine learning classifi...

A novel machine learning based computational framework for homogenization of heterogeneous soft materials: application to liver tissue.

Real-time simulation of organs increases comfort and safety for patients during the surgery. Proper ...

Comparison of Initial Experience with Transrectal Magnetic Resonance Imaging Cognitive Guided Micro-Ultrasound Biopsies versus Established Transperineal Robotic Ultrasound Magnetic Resonance Imaging Fusion Biopsies for Prostate Cancer.

PURPOSE: We compared cancer detection rates in patients who underwent magnetic resonance imaging cog...

Deep learning segmentation of orbital fat to calibrate conventional MRI for longitudinal studies.

In conventional non-quantitative magnetic resonance imaging, image contrast is consistent within ima...

Propagation of uncertainty in the mechanical and biological response of growing tissues using multi-fidelity Gaussian process regression.

A key feature of living tissues is their capacity to remodel and grow in response to environmental c...

Deep learning enables pathologist-like scoring of NASH models.

Non-alcoholic fatty liver disease (NAFLD) and the progressive form of non-alcoholic steatohepatitis ...