VISEM: A Multimodal Video Dataset of Human Spermatozoa

被引：23
|
作者：
Haugen, Trine B. [1 ,2 ]
Hicks, Steven A. [1 ,3 ]
Andersen, Jorunn M. [1 ,2 ]
Witczak, Oliwia [1 ,2 ]
Hammer, Hugo L. [1 ]
Borgli, Rune [4 ]
Halvorsen, Pai [1 ,3 ]
Riegler, Michael [3 ]
机构：
[1] Oslo Metropolitan Univ, Oslo, Norway
[2] Fac Hlth Sci, Oslo, Norway
[3] SimulaMet, Oslo, Norway
[4] Univ Oslo, Oslo, Norway
来源：
PROCEEDINGS OF THE 10TH ACM MULTIMEDIA SYSTEMS CONFERENCE (ACM MMSYS'19) | 2019年
关键词：
Male fertility; Semen analysis; Spermatozoa; Machine Learning; Artificial Intelligence; Videos; Images; Dataset; SEMEN PARAMETERS; QUALITY; FERTILE; POPULATION;
D O I：
10.1145/3304109.3325814
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
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. In this paper, 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 paper 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.
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页码：261 / 266
页数：6
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