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In this study, a method using nano-sized iron particles successfully captured images of sub-dermal hair follicles, showing comparable size and shape to those removed from the skin.

Scientists at the University of Michigan Medical School successfully created a special compound that can be used to improve imaging of prostate cancer.

This study highlights the benefits of virtual surgical planning in orthognathic and facial trauma surgeries, noting its ability to enhance understanding of complex 3D anatomical relationships, reduce operation time, and integrate multidisciplinary approaches, including robotic assistance for real-time adjustments and customized implants.

This review suggests that hyperspectral and terahertz imaging show promise in non-invasively assessing scalp changes associated with hair loss, but further validation is needed for clinical application.

This study explored postpartum body image and menstruation experiences among 11 UK mothers, identifying themes of body dissatisfaction and the stress of resumed menstruation, while highlighting the need for better healthcare support and the positive role of reframing body perceptions towards functionality.

This review outlines the use of quantitative imaging techniques in monitoring tendon response to platelet-rich plasma treatment for chronic tendinopathy and reports that these methods may aid in tailoring PRP protocols.

This study developed a novel Hairless Rag2/Jak3 KO mouse model, which provides superior optical properties and thinner skin compared to existing models, enhancing its utility for noninvasive tumor monitoring and evaluation of anticancer therapies.

In this scoping review, researchers observed that while AI-assisted trichoscopy holds promise for standardized assessments of hair and scalp disorders, its clinical translation is limited by small proprietary datasets, inconsistent validation protocols, and a scarcity of real-world clinical studies.

This study developed a method using Convolutional Neural Networks to detect nutritional deficiencies, such as iron, zinc, biotin, and vitamins, through high-resolution images of hair and nails, achieving an 89% accuracy rate in identifying these deficiencies.

This study proposes a new method for hair segmentation that improved performance in skin lesion images, as indicated by an increase in the Dice score from 76.97% to 79.08%.

This review highlights that two-photon excitation microscopy is a valuable tool for visualizing live skin structures and immune responses at high resolution, though its clinical use is hindered by safety and cost issues.

This study found that 3D imaging may serve as a promising tool for objectively evaluating facial vitiligo repigmentation after treatment with upadacitinib.

In a cross-sectional study, 46% of patients with androgenetic alopecia were found to have depression of borderline to moderate severity, while 62% reported no impact on their quality of life, emphasizing the need for awareness of psychiatric comorbidities among dermatologists.

A deep learning model accurately detects early hair loss signs using scalp images.

This study developed a deep learning model for the automated early detection of androgenetic alopecia using trichoscopic images, and found it demonstrated high accuracy and generalizability in a Korean clinical cohort, achieving a 90% accuracy in external validation.

This study evaluated a new AI-linked imaging device for grading dandruff severity, finding high correlation with expert assessments and suggesting its potential application in other skincare areas due to its versatility and ease of use.

This study developed a convolutional neural network model for non-invasive diagnosis of androgenetic alopecia using dermoscopic images, demonstrating potential accuracy and scalability while highlighting the importance of model interpretability for clinical use.

Mirror-image twins can have alopecia areata on opposite sides of their heads.

In this study, the authors emphasize the importance of not ignoring the partial presence of comma or harpin hairs and black spots when identifying early lesions of tinea capitis, which may initially be overlooked due to their small size.

This study developed a model for detecting sparse hair clusters using enhanced object detection neural networks and medical images, which accurately identifies and counts sparse hair clusters with greater accuracy and efficiency than existing methods.

The model can effectively identify good quality skin images but needs more testing for real-world use.

This study found that among women with female pattern hair loss, higher self-esteem is significantly associated with lower body image concerns and greater self-compassion.

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This study reports that improvements to the EczemaNet pipeline, incorporating pixel-level segmentation and data augmentation, enhanced the reliability and interpretability of assessing atopic dermatitis severity from digital images.

This article discusses tools for measuring hair density in donor areas to guide hair transplant surgery and reports no new clinical results; the authors emphasize the role of digital imaging in achieving consistent outcomes.

This study introduces a novel method for capturing and digitally rendering the color appearance of physical hair samples using deep neural networks.

This study reported that women with polycystic ovarian syndrome are more likely to experience depression and have a poorer body image perception compared to healthy controls.

This study illustrates that low-dose oral minoxidil shows clinically notable hair regrowth, particularly at the crown in male patients, with differing efficacy from bitemporal sites; images document regrowth in a male and a female patient.