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Photography

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CycleGAN-based deep learning technique for artifact reduction in fundus photography.

Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie
PURPOSE: A low quality of fundus photograph with artifacts may lead to false diagnosis. Recently, a cycle-consistent generative adversarial network (CycleGAN) has been introduced as a tool to generate images without matching paired images. Therefore,...

Technological advances for the detection of melanoma: Advances in diagnostic techniques.

Journal of the American Academy of Dermatology
Managing the balance between accurately identifying early stage melanomas while avoiding obtaining biopsy specimens of benign lesions (ie, overbiopsy) is the major challenge of melanoma detection. Decision making can be especially difficult in patien...

Application of deep learning image assessment software VeriSee™ for diabetic retinopathy screening.

Journal of the Formosan Medical Association = Taiwan yi zhi
PURPOSE: To develop a deep learning image assessment software VeriSee™ and to validate its accuracy in grading the severity of diabetic retinopathy (DR).

Artificial Intelligence to Detect Papilledema from Ocular Fundus Photographs.

The New England journal of medicine
BACKGROUND: Nonophthalmologist physicians do not confidently perform direct ophthalmoscopy. The use of artificial intelligence to detect papilledema and other optic-disk abnormalities from fundus photographs has not been well studied.

Efficacy for Differentiating Nonglaucomatous Versus Glaucomatous Optic Neuropathy Using Deep Learning Systems.

American journal of ophthalmology
PURPOSE: We sought to assess the performance of deep learning approaches for differentiating nonglaucomatous optic neuropathy with disc pallor (NGON) vs glaucomatous optic neuropathy (GON) on color fundus photographs by the use of image recognition.

Multi-Person Pose Estimation Using an Orientation and Occlusion Aware Deep Learning Network.

Sensors (Basel, Switzerland)
Image based human behavior and activity understanding has been a hot topic in the field of computer vision and multimedia. As an important part, skeleton estimation, which is also called pose estimation, has attracted lots of interests. For pose esti...

Deep learning computer vision algorithm for detecting kidney stone composition.

BJU international
OBJECTIVES: To assess the recall of a deep learning (DL) method to automatically detect kidney stones composition from digital photographs of stones.

Domain-invariant interpretable fundus image quality assessment.

Medical image analysis
Objective and quantitative assessment of fundus image quality is essential for the diagnosis of retinal diseases. The major factors in fundus image quality assessment are image artifact, clarity, and field definition. Unfortunately, most of existing ...