Article

Using Slit-Lamp Images for Deep Learning–Based Identification of Bacterial and Fungal Keratitis

2021-05-19

Abstract excerpt

In this study, we aimed to develop a deep learning model for identifying bacterial keratitis (BK) and fungal keratitis (FK) by using slit-lamp images. We retrospectively collected slit-lamp images of patients with culture-proven microbial keratitis between January 1, 2010, and December 31, 2019, from two medical centers in Taiwan. We constructed a deep learning algorithm, consisting of a segmentation model for cro...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 4add6fdb-fe95-5991-9af2-419ca18d1174
DOI: 10.20944/preprints202105.0438.v1

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Using Slit-Lamp Images for Deep Learning–Based Identification of Bacterial and Fungal KeratitisDOI 10.20944/preprints202105.0438.v1Read

Determination of probability of causative pathogen in infectious keratitis using deep learning algorithm of slit-lamp imagesSemantic proximity Read

A Tutorial on Automated Classification of Eye Diseases Using Deep LearningSemantic proximity Read

An Open-Source Generalizable Deep Learning Framework for Automated Corneal Segmentation in Anterior Segment Optical Coherence Tomography ImagingSemantic proximity Read

Deep Learning Based on DeepLabv3+ for Automated Identification, Segmentation, and Quantification of Fungi in Clinical Fluorescence Microscopy ImagesSemantic proximity Read

Deep Learning Models for Automated Classification of Seborrheic Keratosis: A Comprehensive Literature Review and Comparative StudySemantic proximity Read

EDNet-20: Enhancing Multi-Label Ocular Disease Detection through Deep Learning OptimizationSemantic proximity Read

Fundus Image Analysis of Retinitis Pigmentosa Using Artificial IntelligenceSemantic proximity Read

Applications of Artificial Intelligence in Optometric Diagnostics: A Review of Techniques and Clinical ImpactSemantic proximity Read

Predicting optical coherence tomography-derived diabetic macular edema grades from fundus photographs using deep learning.Semantic proximity Read

Revolutionizing Corneal Staining Assessment: Advanced Evaluation through Lesion-aware Fine-Grained Knowledge DistillationSemantic proximity Read

Deep Learning Framework for Multiclass Detection of Ocular Diseases in Fundus ImagesSemantic proximity Read

Automated Detection of Elevated Intracranial Pressure via Fundus Image Analysis: A Deep Learning ApproachSemantic proximity Read