VISEM-Tracking is a dataset consisting of 20 video recordings of 30s of spermatozoa with manually annotated bounding-box coordinates and a set of sperm characteristics analyzed by experts in the domain. It is an extension of the previously published VISEM dataset. In addition to the annotated data, unlabeled video clips are provided for easy-to-use access and analysis of the data.

Pre-print and citation:

Pre-print

@article{thambawita2023visem, title={VISEM-Tracking, a human spermatozoa tracking dataset}, author={Thambawita, Vajira and Hicks, Steven A and Stor{\aa}s, Andrea M and Nguyen, Thu and Andersen, Jorunn M and Witczak, Oliwia and Haugen, Trine B and Hammer, Hugo L and Halvorsen, P{\aa}l and Riegler, Michael A}, journal={Scientific Data}, volume={10}, number={1}, pages={1--8}, year={2023}, publisher={Nature Publishing Group} }

Motivation and background

Manual evaluation of a sperm sample using a microscope is time-consuming and requires costly experts who have extensive training. In addition, the validity of manual sperm analysis becomes unreliable due to limited reproducibility and high inter-personnel variations due to the complexity of tracking, identifying, and counting sperms in fresh samples. The existing computer-aided sperm analyzer systems are not working well enough for application in a real clinical setting due to unreliability caused by the consistency of the semen sample. Therefore, we need to research new methods for automated sperm analysis.

Target group

The task is of interest to researchers in the areas of machine learning (classification and detection), visual content analysis, and multimodal fusion. Overall, this task is intended to encourage the multimedia community to help improve the health care system through the application of their knowledge and methods to reach the next level of computer and multimedia-assisted diagnosis, detection, and interpretation.

Class Label Mapping sperm: 0 cluster: 1 small or pinhead: 2

Sperm Detection VISEM

## Overview

Sperm Detection VISEM is a dataset for object detection tasks - it contains Sperm annotations for 9,481 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

Visem

## Overview

Visem is a dataset for object detection tasks - it contains 0 KIdu annotations for 1,449 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

Real multimedia datasets that contain more than just images or text are rare. Even more so are open multimedia datasets in medicine. Often, clinically related datasets only consist of image or videos. We present a dataset that is novel in two ways. Firstly, it is a multi-modal dataset containing different data sources such as videos, biological analysis data, and participant data. Secondly, it is the first dataset of that kind in the field of human reproduction. It consists of anonymized data from 85 different participants. We hope this dataset will inspire people to apply their knowledge in this important field, generate shareable results in the domain, and ultimately improve human infertility investigation and treatment.

VISEM-Tracking-graphs - HuggingFace Repository

This HuggingFace repository contains the pre-generated graphs for the sperm video dataset called VISEM-Tracking (https://huggingface.co/papers/2212.02842) . The graphs represent spatial and temporal relationships between sperm in a video. Spatial edges connect sperms within the same frame, while temporal edges connect sperms across different frames. The graphs have been generated with varying spatial threshold values: 0.1, 0.2, 0.3, 0.4… See the full description on the dataset page: https://huggingface.co/datasets/SimulaMet-HOST/visem-tracking-graphs.

sperm-net/VISEM-Tracking-Plus dataset hosted on Hugging Face and contributed by the HF Datasets community

Visem_yolo2

## Overview

Visem_yolo2 is a dataset for object detection tasks - it contains Sperm annotations for 9,899 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).