AIMC Topic: Microscopy, Confocal

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Multiview confocal super-resolution microscopy.

Nature
Confocal microscopy remains a major workhorse in biomedical optical microscopy owing to its reliability and flexibility in imaging various samples, but suffers from substantial point spread function anisotropy, diffraction-limited resolution, depth-d...

[Artificial intelligence in ex vivo confocal laser scanning microscopy].

Der Hautarzt; Zeitschrift fur Dermatologie, Venerologie, und verwandte Gebiete
BACKGROUND: Visual data, such as clinical photographs or pictures from imaging examination methods, such as ex vivo confocal laser scanning microscopy (CLSM), are particularly suitable for machine learning techniques.

Classification of Basal Cell Carcinoma in Ex Vivo Confocal Microscopy Images from Freshly Excised Tissues Using a Deep Learning Algorithm.

The Journal of investigative dermatology
Ex vivo confocal microscopy (EVCM) generates digitally colored purple-pink images similar to H&E without time-consuming tissue processing. It can be used during Mohs surgery for rapid detection of basal cell carcinoma (BCC); however, reading EVCM ima...

Deep Learning for Basal Cell Carcinoma Detection for Reflectance Confocal Microscopy.

The Journal of investigative dermatology
Basal cell carcinoma (BCC) is the most common skin cancer, with over 2 million cases diagnosed annually in the United States. Conventionally, BCC is diagnosed by naked eye examination and dermoscopy. Suspicious lesions are either removed or biopsied ...

A deep transfer learning framework for the automated assessment of corneal inflammation on in vivo confocal microscopy images.

PloS one
PURPOSE: Infiltration of activated dendritic cells and inflammatory cells in cornea represents an important marker for defining corneal inflammation. Deep transfer learning has presented a promising potential and is gaining more importance in compute...

An open-source semi-automated robotics pipeline for embryo immunohistochemistry.

Scientific reports
A significant challenge for developmental systems biology is balancing throughput with controlled conditions that minimize experimental artifacts. Large-scale developmental screens such as unbiased mutagenesis surveys have been limited in their appli...

Red blood cell phenotyping from 3D confocal images using artificial neural networks.

PLoS computational biology
The investigation of cell shapes mostly relies on the manual classification of 2D images, causing a subjective and time consuming evaluation based on a portion of the cell surface. We present a dual-stage neural network architecture for analyzing fin...

Digital Frozen Sections with Fluorescence Confocal Microscopy During Robot-assisted Radical Prostatectomy: Surgical Technique.

European urology
BACKGROUND: Robot-assisted radical prostatectomy (RARP) involves a tradeoff between oncological control and functional outcomes. Intraoperative control of surgical margins (SMs) may help in ensuring the safety of the dissection. Fluorescence confocal...