AIMC Topic: Photography

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Artificial intelligence-based Raynaud's quantification index (ARTIX): an objective mobile-based tool for patient-centered assessment of Raynaud's phenomenon.

Arthritis research & therapy
BACKGROUND: We aimed to develop an artificial intelligence algorithm able to assess Raynaud's phenomenon (RP) from mobile phone photography, ensuring as a patient-centered, image-based method for RP quantification.

Mobile applications for skin cancer detection are vulnerable to physical camera-based adversarial attacks.

Scientific reports
Skin cancer is one of the most prevalent malignant tumors, and early detection is crucial for patient prognosis, leading to the development of mobile applications as screening tools. Recent advances in deep neural networks (DNNs) have accelerated the...

A Complete Transfer Learning-Based Pipeline for Discriminating Between Select Pathogenic Yeasts from Microscopy Photographs.

Pathogens (Basel, Switzerland)
Pathogenic yeasts are an increasing concern in healthcare, with species like often displaying drug resistance and causing high mortality in immunocompromised patients. The need for rapid and accessible diagnostic methods for accurate yeast identific...

Updated Techniques for Melanoma Diagnosis.

Dermatologic clinics
Melanoma, an aggressive skin cancer, requires timely diagnostics for improved patient outcomes. The ABCDE criteria-assessing asymmetry, borders, color, diameter, and evolution-serve as foundational guidelines for early detection. Non-invasive tools l...

Detecting wing fractures in chickens using deep learning, photographs and computed tomography scanning.

Poultry science
Animal welfare monitoring is a key part of veterinary surveillance in every poultry slaughterhouse. Among the animal welfare indicators routinely inspected, the prevalence of wing fractures and soft tissues injuries (e.g. bruises) is particularly rel...

Functional blepharoptosis screening with generative augmented deep learning from external ocular photography.

Orbit (Amsterdam, Netherlands)
PURPOSE: To develop and validate a deep learning model for the detection of functional blepharoptosis from external ocular photographs, and to quantify the impact of augmenting the training data with synthetic images on model performance.

A digital photography dataset for Vaccinia Virus plaque quantification using Deep Learning.

Scientific data
Virological plaque assay is the major method of detecting and quantifying infectious viruses in research and diagnostic samples. Furthermore, viral plaque phenotypes contain information about the life cycle and spreading mechanism of the virus formin...

Detection of ninhydrin-glyphosate in groundwater via the colour chart-assisted digital camera method.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
This study introduces a novel application of a one-time and multistandard colour chart across three instruments using colour visible spectrophotometer (colour VS), digital single-lens reflex (DSLR) cameras, and mobile camera (MC) analysis to quantify...

Influence of artificial intelligence on ophthalmologists' judgments in glaucoma.

PloS one
PURPOSE: To examine the influence of artificial intelligence (AI) on physicians' judgments regarding the presence and severity of glaucoma on fundus photographs in an online simulation system.

Applications of Machine Learning in Image Analysis to Identify Craniosynostosis: A Systematic Review and Meta-Analysis.

Orthodontics & craniofacial research
Craniosynostosis is a condition characterised by the premature fusion of cranial sutures, which can lead to significant neurodevelopmental and aesthetic issues if not diagnosed and treated early. This study aimed to systematically review and conduct ...