AIMC Topic: Photography

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Colon Disease Classification Method Based on Deep Learning.

Studies in health technology and informatics
Objective Colorectal cancer (CRC) is a common malignant tumor of the digestive system with a high incidence rate. It is prone to misdiagnosis or missed diagnosis in clinical practice. Therefore, researching computer-aided diagnostic methods for endos...

Deep learning-based analysis of infrared fundus photography for automated diagnosis of diabetic retinopathy with cataracts.

Journal of cataract and refractive surgery
PURPOSE: To develop deep learning-based networks for the diagnosis of diabetic retinopathy (DR) with cataracts based on infrared fundus images.

Efficacy of deep learning-based artificial intelligence models in screening and referring patients with diabetic retinopathy and glaucoma.

Indian journal of ophthalmology
PURPOSE: To analyze the efficacy of a deep learning (DL)-based artificial intelligence (AI)-based algorithm in detecting the presence of diabetic retinopathy (DR) and glaucoma suspect as compared to the diagnosis by specialists secondarily to explore...

An Enhanced Synthetic Cystoscopic Environment for Use in Monocular Depth Estimation.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
As technology advances and sensing devices improve, it is becoming more and more pertinent to ensure accurate positioning of these devices, especially within the human body. This task remains particularly difficult during manual, minimally invasive s...

Neurologic Dysfunction Assessment in Parkinson Disease Based on Fundus Photographs Using Deep Learning.

JAMA ophthalmology
IMPORTANCE: Until now, other than complex neurologic tests, there have been no readily accessible and reliable indicators of neurologic dysfunction among patients with Parkinson disease (PD). This study was conducted to determine the role of fundus p...

AutoMorph: Automated Retinal Vascular Morphology Quantification Via a Deep Learning Pipeline.

Translational vision science & technology
PURPOSE: To externally validate a deep learning pipeline (AutoMorph) for automated analysis of retinal vascular morphology on fundus photographs. AutoMorph has been made publicly available, facilitating widespread research in ophthalmic and systemic ...

Investigation of the Role of Convolutional Neural Network Architectures in the Diagnosis of Glaucoma using Color Fundus Photography.

Turkish journal of ophthalmology
OBJECTIVES: To evaluate the performance of convolutional neural network (CNN) architectures to distinguish eyes with glaucoma from normal eyes.