UniDataPro/women-hair-loss-dataset
Bald Women Dataset Dataset comprises 1,080 images of 540 women with alopecia, featuring top-view scalp images paired with segmentation masks. It is designed for machine learning and deep learning applications, focusing on hair follicles, hair density , and scalp health analysis. By leveraging this dataset, researchers and developers can enhance early detection, accurate diagnosis, and personalizing treatment strategies for hair thinning, hair falling, and scalp conditions. -… See the full description on the dataset page: https://huggingface.co/datasets/UniDataPro/women-hair-loss-dataset.
Bald Women Dataset
Dataset comprises 1,080 images of 540 women with alopecia, featuring top-view scalp images paired with segmentation masks. It is designed for machine learning and deep learning applications, focusing on hair follicles, hair density , and scalp health analysis.
By leveraging this dataset, researchers and developers can enhance early detection, accurate diagnosis, and personalizing treatment strategies for hair thinning, hair falling, and scalp conditions. - [Get the data](https://unidata.pro/datasets/hair-loss-in-women-segmentation-dataset/?utm_source=huggingface-org&utm_medium=referral&utm_campaign=women-hair-loss-dataset)
Dataset provides a robust foundation for medical image analysis, machine learning models, and clinical research, enabling advancements in hair loss prevention, regenerating hair, and scalp disease diagnosis.
Frequently Asked Questions
What is this women hair loss dataset used for?
This women hair loss dataset is designed for computer vision research involving hair density analysis, scalp assessment, hair thinning, and alopecia-related image analysis.
What type of segmentation data is included?
Each participant is represented by two related images: a top-view photograph and a corresponding segmentation mask. The top-view perspective provides a direct view of the scalp and hair distribution, while the mask supplies pixel-level information for segmentation experiments. This paired structure allows researchers to train supervised computer vision models that learn the relationship between the original photograph and its target mask.
Why are top-view images useful for hair loss analysis?
Top-view photographs provide a particularly informative perspective for evaluating hair density and visible scalp areas. Unlike frontal portraits, images captured from above expose larger portions of the scalp and make changes in hair coverage easier to analyze spatially.
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Example for the dataset
Each image is annotated with precise segmentation masks, enabling analysis of hair follicles, hair density, and baldness patterns.