Histology permits the observation of otherwise invisible structures of the internal topography
of a specimen. Although it enables the investigation of tissues at a cellular level, it is invasive …

Presented here are the results of an investigation conducted to determine the effectiveness
of deep learning (DL)-based systems utilizing the power of transfer learning for detecting …

Background The current standard of documenting and communicating frozen section margin
results is inefficient. We present a novel method of generating 3D digital models of gross …

Histological brain slices are widely used in neuroscience to study the anatomical
organization of neural circuits. Systematic and accurate comparisons of anatomical data …

Ex vivo imaging enables analysis of the human brain at a level of detail that is not possible
in vivo with MRI. In particular, histology can be used to study brain tissue at the microscopic …

Two-dimensional (2D) histopathology based on the observation of thin tissue slides is the
current paradigm in diagnosis and prognosis. However, labeling strategies in conventional …

The VERDICT framework for modelling diffusion MRI data aims to relate parameters from a
biophysical model to histological features used for tumour grading in prostate cancer …

The presence of lymphovascular invasion (LVI) in urothelial carcinoma (UC) is a poor
prognostic finding. This is difficult to identify on routine hematoxylin–eosin (H&E)-stained …

Three-dimensional (3D) bioprinting is an emerging tissue engineering technology, already
with several remarkable accomplishments and with more promises to fulfill. Besides the …

Medical imaging often presents objects in three-dimensional (3D) form to provide better
visual understanding. In contrast, histopathology is typically presented as two-dimensional …