paper-with-me

홈 › Papers

A prospectus on the surface metrology of seborrheic keratoses

2024-09-21 · Nicole Werpachowski, Juliette Nutovits, Therese Limbana, John Goncalves, Alina Bridges, Brian Lee Beatty

Background: Human skin texture has yet to be quantified for diagnostic purposes. Here, the surface metrology of seborrheic keratoses is investigated with an optical profiler. Materials and Methods: Dermatologic specimens of 7 cadavers were prepared. Specimens were molded with polyvinyl siloxane and casts prepared with resin, which were scanned using a 3D white light optical profiler. Each scan produced 48 variables, categorized into 3 groups for each location: control, lesion center, and lesion edge. Images of the histopathology slides for suspected seborrheic keratoses were reviewed by a dermatopathologist. Results: The parameters under investigation included border versus center of keratoses, age, sex, lesion location, degree of sun exposure, and cause of death. Although some parameters differ between individuals and age groups, the majority of differences identified between the roughness parameters measured are a result of sex, sun exposure, and histological diagnosis, listed in order of increasing importance. Histological diagnosis provided the most significant, definitive number of individual measurements of areas of roughness in seborrheic keratoses in comparison to other parts of the skin (regardless if those were controls or a different pigmented lesion aside from seborrheic keratoses). Conclusions: This study demonstrates that there are quantifiable patterns of surface textures that can be compared between keratotic and standard normal skin surfaces. These findings suggest this method has the potential to be applied as a noninvasive adjunct to current methods of dermatological diagnosis.

📄 PDF Abstract BibTeX arXiv:2409.14250

Code (0)

등록된 구현이 없습니다.

Tasks

Diagnostic

Similar Papers 제목 키워드 기반

Evaluating Machine Learning-based Skin Cancer Diagnosis

2024-09-04 · Tanish Jain

This study evaluates the reliability of two deep learning models for skin cancer detection, focusing on their explainability and fairness. Using the HAM10000 dataset of dermatoscopic images, the research assesses two con…

Fairness

Surface Metrology of Cerebral Arteries Luminal Surface

2023-03-22 · Jennifer Buoncore, Alexis Sobecki, Brian Lee Beatty

Atherosclerotic lesions within carotid and cerebral vessels are likely to influence hemodynamics and manifest into vascular pathologies, including Alzheimers Disease and ischemic stroke. Hemodynamics are influenced by ch…

Robots That Generate Planarity Through Geometry

2026-02-06 · Jakub F. Kowalewski, Abdulaziz O. Alrashed, Jacob Alpert, Rishi Ponnapalli 외 arxiv

Constraining motion to a flat surface is a fundamental requirement for equipment across science and engineering. Modern precision robotic motion systems, such as gantries, rely on the flatness of components, including gu…

Contrasting results of surface metrology techniques for three-dimensional human fingerprints

2024-10-16 · Brian Lee Beatty, Shani Kahan, Burcak Bas, Bettina Zou 외

Fingerprints, otherwise known as dermatoglyphs, are most commonly thought of in the context of identification, but have myriad other roles in human biology. They are formed by the restricted ability of ridges and furrows…

Image Classification of Melanoma, Nevus and Seborrheic Keratosis by Deep Neural Network Ensemble

2017-03-09 · Kazuhisa Matsunaga, Akira Hamada, Akane Minagawa, Hiroshi Koga

This short paper reports the method and the evaluation results of Casio and Shinshu University joint team for the ISBI Challenge 2017 - Skin Lesion Analysis Towards Melanoma Detection - Part 3: Lesion Classification host…

General Classificationimage-classificationImage ClassificationLesion Classification