What is the Skin Cancer (ISIC Images) Dataset?

The dataset contains balanced dermoscopic images of benign and malignant skin lesions curated for AI-based skin cancer detection, classification, and medical research applications.

How can this dataset be used in AI and machine learning projects?

It supports supervised learning for lesion classification, image segmentation, anomaly detection, and deep learning model training using CNN architectures for diagnostic support systems and telemedicine solutions.

Does GTS provide custom medical image dataset collection and annotation?

Yes. GTS offers custom medical image data collection across diverse age groups, ethnicities, and geographic regions. Services include expert annotation, segmentation, disease labeling, multilingual metadata tagging, and scalable workforce deployment for healthcare AI projects.

What quality assurance and compliance standards does GTS follow?

GTS follows ISO 9001:2015 and ISO 27001:2013 certified quality management systems. All datasets undergo multi-level quality checks, validation, and rework processes. We ensure GDPR and HIPAA compliance with secure data cleaning and privacy-focused handling.

What formats and scalability options are available?

Datasets are delivered in JPEG/PNG image formats with JSON or CSV annotations. GTS supports large-scale enterprise projects, custom annotation schemas, integration-ready formats, and secure global delivery tailored to healthcare AI workflows.

Skin Cancer (ISIC Images)

Datasets

File

Skin Cancer (ISIC Images)

Use Case

Skin Cancer (ISIC Images)

Description

Explore the Skin Spots Classification Dataset featuring balanced images of benign and malignant skin lesions, perfect for AI model development, transfer learning, and dermatological research.

Description:

A balanced dataset of benign (healthy) and malignant (infected) skin spots, ideal for developing and testing AI models using transfer learning and CNNs for skin lesion classification.

Download Dataset

The Skin Spots Classification Dataset is a balanced collection of images, meticulously categorized into two groups: benign (healthy) and malignant (infected) skin spots. This dataset is an invaluable resource for researchers and developers working on dermatological image analysis, machine learning, and computer vision.

Key Features:

Balanced Categories:
- Benign Skin Spots: Representing healthy skin conditions.
- Malignant Skin Spots: Depicting infected or diseased skin areas.
Ideal for AI Applications:
- Supports transfer learning and convolutional neural networks (CNNs) for image classification tasks.
- Enables training of accurate models for early skin disease detection.
Research-Ready:
- Offers a controlled environment to develop, evaluate, and benchmark skin lesion classification algorithms.

This dataset is sourced from Kaggle.

Contact Us

Let's Discuss your Data collection Requirement With Us

To get a detailed estimation of requirements please reach us.

Skin Cancer (ISIC Images)