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Related Experiment Video

Updated: May 7, 2026

SCAnED - An Open-source Skin Segmentation Macro for Semi-automated Cell and Nuclei Detection in Epidermal and Dermal Skin Compartments

SCAnED - An Open-source Skin Segmentation Macro for Semi-automated Cell and Nuclei Detection in Epidermal and Dermal Skin Compartments

Published on: August 8, 2025

PH² - a dermoscopic image database for research and benchmarking.

Teresa Mendonca, Pedro M Ferreira, Jorge S Marques

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference

|October 11, 2013

Summary

This summary is machine-generated.

A new public dermoscopic image database, PH², is introduced to enable fair benchmarking of computer-aided melanoma diagnosis systems. This resource aids research by providing annotated images for evaluating diagnostic algorithm performance.

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Area of Science:

Dermatology
Medical Imaging
Computer-Aided Diagnosis

Background:

Rising melanoma incidence necessitates improved diagnostic tools.
Current computer-aided diagnosis systems lack standardized evaluation due to absent public databases.
Performance comparison of melanoma classification algorithms is hindered.

Purpose of the Study:

To present the PH² database, a novel resource for dermoscopic image analysis.
To facilitate standardized research and benchmarking of computer-aided diagnosis systems for melanoma.
To provide a publicly available dataset for evaluating diagnostic algorithms.

Main Methods:

Compilation of 200 dermoscopic images.
Manual segmentation of images by expert dermatologists.
Inclusion of clinical diagnosis and dermoscopic structure identification for each image.

Main Results:

The PH² database contains 200 annotated dermoscopic images.
Expert dermatologists provided manual segmentation and diagnoses.
Detailed annotations include clinical diagnosis and dermoscopic structures.

Conclusions:

The PH² database offers a valuable resource for melanoma research.
Availability of this database will enable fair performance evaluation of diagnostic systems.
This initiative supports the advancement of computer-aided melanoma diagnosis.