Pathology

On the generalizability of diffusion MRI signal representations across acquisition parameters, sequences and tissue types: Chronicles of the MEMENTO challenge.

Diffusion MRI (dMRI) has become an invaluable tool to assess the microstructural organization of brain tissue. Depending on the specific acquisition settings, the dMRI signal encodes specific properties of the underlying diffusion process. In the last two decades, several signal representations have been proposed to fit the dMRI signal and decode such properties. Most methods, however, are tested ...

Impact of Artificial Intelligence Decision Support Using Deep Learning on Breast Cancer Screening Interpretation with Single-View Wide-Angle Digital Breast Tomosynthesis.

Background The high volume of data in digital breast tomosynthesis (DBT) and the lack of agreement on how to best implement it in screening programs makes its use challenging. Purpose To compare radiologist performance when reading single-view wide-angle DBT images with and without an artificial intelligence (AI) system for decision and navigation support. Materials and Methods A retrospective obs...

Evaluating the Efficacy of Povidone-Iodine Solution Infection Prophylaxis in Immediate Tissue Expander-Based Breast Reconstruction: A Controlled Retrospective Analysis.

There is currently no consensus among plastic surgeons regarding the optimal infection prophylaxis for immediate tissue expander placement following ...

Urine cell image recognition using a deep-learning model for an automated slide evaluation system.

OBJECTIVES: To develop a classification system for urine cytology with artificial intelligence (AI) using a convolutional neural network algorithm tha...

Intraoperative assessment of canine soft tissue sarcoma by deep learning enhanced optical coherence tomography.

Soft tissue sarcoma (STS) is a locally aggressive and infiltrative tumour in dogs. Surgical resection is the treatment of choice for local tumour cont...

Toward autonomous robotic prostate biopsy: a pilot study.

PURPOSE: We present the validation of PROST, a robotic device for prostate biopsy. PROST is designed to minimize human error by introducing some auton...

A BERT model generates diagnostically relevant semantic embeddings from pathology synopses with active learning.

BACKGROUND: Pathology synopses consist of semi-structured or unstructured text summarizing visual information by observing human tissue. Experts write...

Asbestos Detection with Fluorescence Microscopy Images and Deep Learning.

Fluorescent probes can be used to detect various types of asbestos (serpentine and amphibole groups); however, the fiber counting using our previously...

Management of urethral strictures and stenosis caused by the endo-urological treatment of benign prostatic hyperplasia-a single-center experience.

OBJECTIVE: Urethral stricture disease after endo-urological treatment of benign prostatic hyperplasia (BPH) is a sparsely described complication. We d...

Characterizing the Impact of Spray Dried Particle Morphology on Tablet Dissolution Using Quantitative X-Ray Microscopy.

For oral solid dosage forms, disintegration and dissolution properties are closely related to the powders and particles used in their formulation. How...

Convolutional neural networks for cytoarchitectonic brain mapping at large scale.

Human brain atlases provide spatial reference systems for data characterizing brain organization at different levels, coming from different brains. Cy...

Prediction of skin disease using a new cytological taxonomy based on cytology and pathology with deep residual learning method.

With the development of artificial intelligence, technique improvement of the classification of skin disease is addressed. However, few study concerne...

Automated Extraction of Phenotypic Leaf Traits of Individual Intact Herbarium Leaves from Herbarium Specimen Images Using Deep Learning Based Semantic Segmentation.

With the increase in the digitization efforts of herbarium collections worldwide, dataset repositories such as iDigBio and GBIF now have hundreds of t...

Deep Learning-Based Magnetic Resonance Imaging Image Features for Diagnosis of Anterior Cruciate Ligament Injury.

To study and explore the adoption value of magnetic resonance imaging (MRI) in the diagnosis of anterior cruciate ligament (ACL) injuries, a multimoda...

Grading of invasive breast carcinoma: the way forward.

Histologic grading has been a simple and inexpensive method to assess tumor behavior and prognosis of invasive breast cancer grading, thereby identify...

Extended Kalman filter for online soft tissue characterization based on Hunt-Crossley contact model.

Real-time soft tissue characterization is significant to robotic assisted minimally invasive surgery for achieving precise haptic control of robotic s...

Mosquito species identification using convolutional neural networks with a multitiered ensemble model for novel species detection.

With over 3500 mosquito species described, accurate species identification of the few implicated in disease transmission is critical to mosquito borne...

Optical tissue clearing and machine learning can precisely characterize extravasation and blood vessel architecture in brain tumors.

Precise methods for quantifying drug accumulation in brain tissue are currently very limited, challenging the development of new therapeutics for brai...

Time-frequency time-space long short-term memory networks for image classification of histopathological tissue.

Image analysis in histopathology provides insights into the microscopic examination of tissue for disease diagnosis, prognosis, and biomarker discover...

Traction force microscopy by deep learning.

Cells interact mechanically with their surroundings by exerting and sensing forces. Traction force microscopy (TFM), purported to map cell-generated f...