task_categories:image-classification license:cc-by-sa-4.0 size_categories:1K<n<10K format:parquet modality:tabular library:datasets library:pandas library:mlcroissant library:polars region:us
---
dataset_info:
  features:
  - name: image
    sequence:
      sequence: uint8
  - name: head
    dtype: uint8
  - name: vacuole
    dtype: uint8
  - name: acrosome
    dtype: uint8
  splits:
  - name: train
    num_bytes: 4359000
    num_examples: 1000
  - name: valid
    num_bytes: 1046160
    num_examples: 240
  - name: test
    num_bytes: 1307700
    num_examples: 300
  download_size: 4962520
  dataset_size: 6712860
license: cc-by-sa-4.0
task_categories:
- image-classification
pretty_name: The Modified Human Sperm Morphology Analysis Dataset
---
# MHSMA: The Modified Human Sperm Morphology Analysis Dataset

The MHSMA dataset is a collection of human sperm images from 235 patients with male factor infertility. Each image is labeled by experts for normal or abnormal sperm acrosome, head, vacuole, and tail.

# Source
Make sure to visit the [Github page](https://github.com/soroushj/mhsma-dataset). 
```
@article{javadi2019novel,
  title={A novel deep learning method for automatic assessment of human sperm images},
  author={Javadi, Soroush and Mirroshandel, Seyed Abolghasem},
  journal={Computers in Biology and Medicine},
  volume={109},
  pages={182--194},
  year={2019},
  doi={10.1016/j.compbiomed.2019.04.030}
}
```