research Quantifying Alopecia Areata via Texture Analysis to Automate the SALT Score Computation
Researchers created a fast, accurate computer program to measure hair loss in alopecia areata patients.
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research 198 Reliable and interpretable segmentation for remote assessment of atopic dermatitis severity using digital images
The improved EczemaNet more reliably and clearly identifies and assesses the severity of atopic dermatitis from photos.
research CHROMALENS PRECISION MAPPING AS AN INNOVATIVE SYSTEM FOR MICROZONAL HAIR ANALYSIS: STRUCTURE, ALGORITHM, AND COMPARISON WITH CLASSICAL COLORING TECHNIQUES
research Bias Assessment and Data Drift Detection in Medical Image Analysis: A Survey
Reliable machine learning in medical imaging needs bias checks and data drift detection for consistent performance.
research DETECTION OF HAIR FALL AND SCALP DISORDERS THROUGH ML AND IMAGE PROCESSING
AI can effectively detect hair and scalp disorders from images.
research Imaging Tools for Noninvasive Hair Assessment
New imaging tools help doctors better examine hair and scalp health without surgery.
research Optimized polycystic ovarian disease prognosis and classification using AI based computational approaches on multi-modality data
AI can improve early diagnosis and classification of PCOS, aiding in prevention of related health issues.
research 596 Application of an artificial intelligence (AI) photographic device to track platelet-rich plasma treatment outcomes in females with alopecia
An AI photographic device effectively tracked hair growth improvements in women treated for hair loss.
research Trichoscopy of Alopecia Areata: Hair Loss Feature Extraction and Computation Using Grid Line Selection and Eigenvalue
Researchers developed an algorithm for self-diagnosing scalp conditions with high accuracy using smart device-attached microscopes.
research 42063 Image Quality Assessment using Convolutional Neural Network in Clinical Skin Images
The model can effectively identify good quality skin images but needs more testing for real-world use.
research Using artificial intelligence to compute Severity of Alopecia Tool scores
AI can accurately measure hair loss severity in alopecia areata.
research An Automatic AI‐Based Algorithm That Grades the Scalp Surface Exfoliating Process From Video Imaging. Application to Dandruff Severity and Its Validation on Subjects of Different Ages and Ethnicities
The AI device accurately grades scalp exfoliation and can help diagnose scalp disorders.
research Objective quantification of chemotherapy-induced madarosis: a pilot study of an automated computer vision pipeline for eyebrow density assessment
The tool accurately tracks eyebrow hair loss in chemotherapy patients.
research Advancing Hair Loss Assessment in Alopecia Areata: The Mathematical Case for Centralised, Standardised Imaging
Centralized imaging provides more accurate and consistent hair loss measurements in alopecia areata.
research 画像解析による抗がん剤脱毛頭皮の形態構造の検証
Image analysis can effectively identify changes in scalps affected by chemotherapy-induced hair loss.
research ZASTOSOWANIE SZTUCZNEJ INTELIGENCJI W ECHOGRAFII SERCOWEJ: KORZYŚCI I RYZYKO
AI in heart scans improves diagnosis and treatment but has risks like misdiagnosis and high costs.
research Flow-guided hair removal for automated skin lesion identification
The new method removes hair from skin images quickly and accurately to help identify skin lesions better.
research Feature identification of skin diseases and laser therapy with a portable optical coherence imaging system
A portable imaging system shows promise for diagnosing skin diseases and checking laser treatment effects.
research เครองมอประมวลผลภาพดจทลสำหรบวดขอมลของเสนผมบนหนงศรษะของผปวยโรคผมบางทางพนธกรรม
The tool accurately measures hair count and size on scalps with 79.45% and 68.19% accuracy, respectively.
research Analysis of trichoscopic images using deep neural networks for the diagnosis and activity assessment of alopecia areata – a retrospective study
AI can accurately diagnose and assess alopecia areata using scalp images.
research A New Technique for Quantitative Analysis of Hair Loss in Mice Using Grayscale Analysis
Researchers developed a new, precise method to measure hair loss in mice using image analysis.
research 52252 Analysis of basal cell carcinoma and trichoepithelioma with digital spatial profiling
research ISID0199 – Computer vision AI-based androgenetic alopecia analysis using a novel mobile web app.
research Improved Hidden Markov Algorithm Based on Bayes in Low Dose CT Images
The improved algorithm enhances low-dose CT image quality significantly better than other methods.
research Detection of Meibomian Gland Dysfunction by in vivo Confocal Microscopy Based on Deep Convolutional Neural Network
The model can effectively help diagnose meibomian gland dysfunction automatically.
research 18 Digital Imaging and Other Ancillary Tools for Hair Transplantation Evaluation
Digital imaging tools help accurately assess hair transplant candidates.
research Immunofluorescence Tomography: High-resolution 3-D reconstruction by serial-sectioning of methacrylate embedded tissues and alignment of 2-D immunofluorescence images
Immunofluorescence tomography is a cost-effective method for creating detailed 3-D images of tissues.
research “TRICHOASSIST” Trichogram Hair and Scalp Feature Extraction and Analysis Using Image Processing
"TRICHOASSIST" is a system that analyzes hair and scalp images to help diagnose scalp diseases.
research 268 Use of ultra-fast one-step CK5 ihc for identifying bcc and scc during mohs surgery
A new one-step test can quickly identify skin cancer during surgery.
research Rethinking pattern hair loss classification in the era of trichoscopy and artificial intelligence
A hybrid model using traditional methods, trichoscopy, and AI improves hair loss assessment.