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Supervised method for cell counting from bright field focus stacks

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Supervised method for cell counting from bright field focus stacks. / Liimatainen, Kaisa; Ruusuvuori, Pekka; Latonen, Leena; Huttunen, Heikki.

2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI) . IEEE, 2016. p. 391-394.

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Harvard

Liimatainen, K, Ruusuvuori, P, Latonen, L & Huttunen, H 2016, Supervised method for cell counting from bright field focus stacks. in 2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI) . IEEE, pp. 391-394, IEEE INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING, 1/01/00. https://doi.org/10.1109/ISBI.2016.7493290

APA

Liimatainen, K., Ruusuvuori, P., Latonen, L., & Huttunen, H. (2016). Supervised method for cell counting from bright field focus stacks. In 2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI) (pp. 391-394). IEEE. https://doi.org/10.1109/ISBI.2016.7493290

Vancouver

Liimatainen K, Ruusuvuori P, Latonen L, Huttunen H. Supervised method for cell counting from bright field focus stacks. In 2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI) . IEEE. 2016. p. 391-394 https://doi.org/10.1109/ISBI.2016.7493290

Author

Liimatainen, Kaisa ; Ruusuvuori, Pekka ; Latonen, Leena ; Huttunen, Heikki. / Supervised method for cell counting from bright field focus stacks. 2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI) . IEEE, 2016. pp. 391-394

Bibtex - Download

@inproceedings{32f3a67593df42eb80ec87e9d42ec595,
title = "Supervised method for cell counting from bright field focus stacks",
abstract = "We present a novel method for cell counting using bright field focus stacks. Our method is based on the use of supervised learning and out-of-focus appearance of cells. Logistic regression was used for classification with intensity values of 25 focal planes as features. Binary erosion with a large circular structuring element was applied as post-processing step. With this simple method we obtained mean F\-score of 0.87 for cell counting with 12 test images, including images of extremely dense populations. The most important features were obtained from out-of-focus images. Thus, we conclude that using several focal planes provides valuable intensity information for cell counting from bright field microscopy.",
keywords = "Cells & molecules, Confocal, Fluorescence, Image segmentation, Microscopy - Light",
author = "Kaisa Liimatainen and Pekka Ruusuvuori and Leena Latonen and Heikki Huttunen",
year = "2016",
month = "6",
day = "15",
doi = "10.1109/ISBI.2016.7493290",
language = "English",
isbn = "9781479923502",
publisher = "IEEE",
pages = "391--394",
booktitle = "2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI)",

}

RIS (suitable for import to EndNote) - Download

TY - GEN

T1 - Supervised method for cell counting from bright field focus stacks

AU - Liimatainen, Kaisa

AU - Ruusuvuori, Pekka

AU - Latonen, Leena

AU - Huttunen, Heikki

PY - 2016/6/15

Y1 - 2016/6/15

N2 - We present a novel method for cell counting using bright field focus stacks. Our method is based on the use of supervised learning and out-of-focus appearance of cells. Logistic regression was used for classification with intensity values of 25 focal planes as features. Binary erosion with a large circular structuring element was applied as post-processing step. With this simple method we obtained mean F\-score of 0.87 for cell counting with 12 test images, including images of extremely dense populations. The most important features were obtained from out-of-focus images. Thus, we conclude that using several focal planes provides valuable intensity information for cell counting from bright field microscopy.

AB - We present a novel method for cell counting using bright field focus stacks. Our method is based on the use of supervised learning and out-of-focus appearance of cells. Logistic regression was used for classification with intensity values of 25 focal planes as features. Binary erosion with a large circular structuring element was applied as post-processing step. With this simple method we obtained mean F\-score of 0.87 for cell counting with 12 test images, including images of extremely dense populations. The most important features were obtained from out-of-focus images. Thus, we conclude that using several focal planes provides valuable intensity information for cell counting from bright field microscopy.

KW - Cells & molecules

KW - Confocal

KW - Fluorescence

KW - Image segmentation

KW - Microscopy - Light

U2 - 10.1109/ISBI.2016.7493290

DO - 10.1109/ISBI.2016.7493290

M3 - Conference contribution

SN - 9781479923502

SP - 391

EP - 394

BT - 2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI)

PB - IEEE

ER -