AIMC Topic: Optical Imaging

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Deep Learning in Biomedical Optics.

Lasers in surgery and medicine
This article reviews deep learning applications in biomedical optics with a particular emphasis on image formation. The review is organized by imaging domains within biomedical optics and includes microscopy, fluorescence lifetime imaging, in vivo mi...

Real-time intraoperative glioma diagnosis using fluorescence imaging and deep convolutional neural networks.

European journal of nuclear medicine and molecular imaging
PURPOSE: Surgery is the predominant treatment modality of human glioma but suffers difficulty on clearly identifying tumor boundaries in clinic. Conventional practice involves neurosurgeon's visual evaluation and intraoperative histological examinati...

Development of an algorithm for intraoperative autofluorescence assessment of parathyroid glands in primary hyperparathyroidism using artificial intelligence.

Surgery
BACKGROUND: Previous work showed that normal and abnormal parathyroid glands exhibit different patterns of autofluorescence, with the former appearing brighter and more homogenous. However, an objective algorithm based on quantified measurements was ...

A microfluidic robot for rare cell sorting based on machine vision identification and multi-step sorting strategy.

Talanta
The identification, sorting and analysis of rare target single cells in human blood has always been a clinically meaningful medical challenge. Here, we developed a microfluidic robot platform for sorting specific rare cells from complex clinical bloo...

Deep learning-based classification of retinal atrophy using fundus autofluorescence imaging.

Computers in biology and medicine
PURPOSE: To automatically classify retinal atrophy according to its etiology, using fundus autofluorescence (FAF) images, using a deep learning model.

Cell segmentation and tracking using CNN-based distance predictions and a graph-based matching strategy.

PloS one
The accurate segmentation and tracking of cells in microscopy image sequences is an important task in biomedical research, e.g., for studying the development of tissues, organs or entire organisms. However, the segmentation of touching cells in image...

Spatially Aware Dense-LinkNet Based Regression Improves Fluorescent Cell Detection in Adaptive Optics Ophthalmic Images.

IEEE journal of biomedical and health informatics
Retinal pigment epithelial (RPE) cells play an important role in nourishing retinal neurosensory photoreceptor cells, and numerous blinding diseases are associated with RPE defects. Their fluorescence signature can now be visualized in the living hum...

Current Trends in Artificial Intelligence Application for Endourology and Robotic Surgery.

The Urologic clinics of North America
With the advent of electronic medical records and digitalization of health care over the past 2 decades, artificial intelligence (AI) has emerged as an enabling tool to manage complex datasets and deliver streamlined data-driven patient care. AI algo...

A deep learning approach in diagnosing fungal keratitis based on corneal photographs.

Scientific reports
Fungal keratitis (FK) is the most devastating and vision-threatening microbial keratitis, but clinical diagnosis a great challenge. This study aimed to develop and verify a deep learning (DL)-based corneal photograph model for diagnosing FK. Corneal ...

Radiomics and Deep Learning from Research to Clinical Workflow: Neuro-Oncologic Imaging.

Korean journal of radiology
Imaging plays a key role in the management of brain tumors, including the diagnosis, prognosis, and treatment response assessment. Radiomics and deep learning approaches, along with various advanced physiologic imaging parameters, hold great potentia...