Sperm Morphology Image Data Set (SMIDS)

SMIDS was collected by a smartphone based data acquisition approach, which has been firstly used in [1] for only motile sperm detection and counting scope. Then, smartphone based this approach has been validated in sperm concentration analysis with high correlation between the manual counting results and the system output [2]. Addition to motile sperm detection/counting and concentration analysis, system was also used for creating a stained sperm image dataset, which named as SMIDS. The full version of SMIDS was firstly introduced in [3] with a hybrid morphological analyzing framework. In SMIDS, the abnormal class is not divided into the sub-classes as in other sperm morphology datasets. Sperm images were labelled as normal (1021), abnormal (1005) and non-sperm (974). The images are stored in RGB color-space. Each image in SMIDS might include noise, multi-sperm head and mixed tails. [1] Ilhan, H. O., & Aydin, N. (2018). A novel data acquisition and analyzing approach to spermiogram tests. Biomedical Signal Processing and Control, 41, 129-139. [2] Ilhan, H. O., & Aydin, N. (2020). Smartphone based sperm counting-an alternative way to the visual assessment technique in sperm concentration analysis. Multimedia Tools and Applications, 79(9), 6409-6435. [3] Ilhan, H. O., Sigirci, I. O., Serbes, G., & Aydin, N. (2020). A fully automated hybrid human sperm detection and classification system based on mobile-net and the performance comparison with conventional methods. Medical & biological engineering & computing, 58(5), 1047-1068.