Commercial

Women Hair Loss Segmentation Dataset

This hair loss dataset features annotated images of women with varying degrees of hair loss, designed for machine learning and deep learning applications focused on analyzing hair density, scalp conditions, and developing solutions for hair restoration, hair thinning, and alopecia treatment

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  • Images
    1 080
  • People
    540
  • Computer Vision
  • Medicine
  • Classification
  • Machine Learning
  • Segmentation
  • Images
    1 080
  • People
    540

Dataset Info

Characteristic Data
Description Photos of women with varying degrees of hair loss for segmentation tasks
Data types Image
Tasks Classification, Machine Learning
Number of images 1 080
Number of files in a set 2 images for women (image from the top + mask)
Total number of people 540
Labeling Metadata (gender, age, ethnicity)
Age Min = 18, max = 80, mean = 45
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Technical
Characteristics

Characteristic Data
Image Extensions Png, jpeg
Mask Extension Png
Source and collection methodology: Data was collected via crowdsourcing platforms.

Dataset Use Cases

  • Medical Research & Dermatology

    Analyzing Hair Loss Patterns in Women

    Women Hair Loss Dataset provides detailed medical images that help dermatologists study hair thinning, hair density, and scalp conditions. With segmentation masks highlighting affected areas, researchers can track hairs loss progression and evaluate hair loss treatments. This supports early detection of hair disorders and more effective treatment strategies.



  • Machine Learning & AI Development

    Training Models for Hair Loss Segmentation

    This hair loss segmentation dataset is designed for machine learning and deep learning applications. Containing a carefully annotated bald images dataset, it enables learning models to classify hair textures, measure scalp health, and detect alopecia stages. Models trained with this data achieve accurate diagnosis, helping advance medical AI solutions.



  • Pharmaceutical & Cosmetic Industry

    Developing Hair Restoration and Care Products

    Cosmetic brands and pharmaceutical companies use the alopecia dataset to evaluate hair restoration products and hair care treatments. By analyzing hair follicles, natural hairs, and scalp health, they design more effective hair transplants, hair growth serums, and thicker hair solutions tailored to different skin types and hair disorders.



  • Education & Clinical Training

    Supporting Training in Dermatology and Diagnosis

    Medical schools and clinics apply the bald women dataset for teaching students how to identify hair falling, scalp diseases, and alopecia progression. The dataset’s manual segmentation masks allow trainees to practice diagnosing hair conditions, ensuring they gain practical experience in recognizing skin diseases and recommending targeted loss treatments.



FAQs

What is included in Women Hair Loss Segmentation Dataset?
It consists of 1,080 images from 540 women, each set containing a photo from the top view and a corresponding segmentation mask. Additionally, it includes metadata files with details such as age, gender, and ethnicity, supporting scalp condition analysis and AI training datasets.
What types of annotations are provided?
Each image includes a segmentation mask in PNG format that highlights areas of hair thinning or baldness. Metadata annotations cover age, gender, and ethnicity, allowing researchers to study different types of scalp conditions and create models trained with high accuracy.
What age groups are represented in this dataset?
The dataset covers women aged 18 to 80, with an average age of 45 years. This wide age range helps train learning models that can detect hair falling, scalp conditions, and hair density changes across different life stages.
What are the sources of data for this dataset?
The images were collected via trusted crowdsourcing platforms with strict quality control measures. All data was ethically sourced, featuring women with different hair loss conditions.
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