Deep learning-based method for segmenting epithelial layer of tubules in histopathological images of testicular tissue.

Azadeh Fakhrzadeh¹, Pouya Karimian², Mahsa Meyari², Cris L Luengo Hendriks³, Lena Holm⁴, Christian Sonne⁵, Rune Dietz⁵, Ellinor Spörndly-Nees⁶

¹Iranian Research Institute for Information Science and Technology, Information Technology Department, Tehran, Iran.

²Amirkabir University of Technology (Tehran Polytechnic), Industrial Engineering and Management Systems Department, Tehran, Iran.

³Deepcell, Inc., Menlo Park, California, United States.

⁴Swedish University of Agricultural Sciences, Department of Anatomy, Physiology, and Biochemistry, Uppsala, Sweden.

⁵Aarhus University, Arctic Research Centre, Department of Ecoscience, Roskilde, Denmark.

⁶National Veterinary Institute, Department of pathology and wildlife Diseases, Uppsala, Sweden.

PubMed PMC DOI PDF

Abstract

PURPOSE: There is growing concern that male reproduction is affected by environmental chemicals. One way to determine the adverse effect of environmental pollutants is to use wild animals as monitors and evaluate testicular toxicity using histopathology. We propose an automated method to process histology images of testicular tissue. APPROACH: Testicular tissue consists of seminiferous tubules. S…

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