Additional file 4 of Micro-CT and machine learning: a high-throughput alternative to histology for follicle reserve assessment in cryopreserved ovarian tissue

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Authors: Katri Knuus, Mai Nguyen, Markus Hannula, Jasmin Hassan, Marjut Otala, Timo Tuuri, Karolina Lundin, Atte Lahtinen, Pauliina Damdimopoulou, Jari Hyttinen, Kirsi Jahnukainen
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Abstract

Additional file 4. Additional Figure 3. Influence of sectioning interval on histological estimation of oocyte density. Representative images from one adult sample (A1) and one child sample (C2) illustrate oocyte density derived from 3D micro-CT analysis (red line) compared with virtual section-based oocyte density estimates obtained with (black line) and without (green line) application of the correction algorithm (11). Density estimates without correction are substantially overestimated due to repeated counting of individual oocytes. Application of the correction algorithm reduces this artifact, yielding values that closely approximate the true 3D-derived oocyte density.

Fields of Study & Subjects

Reproductive Biology and Fertility Ovarian function and disorders Reproductive biology and impacts on aquatic species

Publication details

Journal / source
Figshare
Publication date
1 January 2026