Weakly-supervised prediction of cell migration modes in confocal microscopy images using bayesian deep learning

Gupta, AnindyaUppsala universitet,Avdelningen för visuell information och interaktion,Science for Life Laboratory, SciLifeLab,Bildanalys och människa-datorinteraktion,Centre for Image Analysis (author)

Cell migration is pivotal for their development, physiology and disease treatment. A single cell on a 2D surface can utilize continuous or discontinuous migration modes. To comprehend the cell migration, an adequate quantification for single cell-based analysis is crucial. An automatized approach could alleviate tedious manual analysis, facilitating large-scale drug screening. Supervised deep learning has shown promising outcomes in computerized microscopy image analysis. However, their implication is limited due to the scarcity of carefully annotated data and uncertain deterministic outputs. We compare three deep learning models to study the problem of learning discriminative morphological representations using weakly annotated data for predicting the cell migration modes. We also estimate Bayesian uncertainty to describe the confidence of the probabilistic predictions. Amongst three compared models, DenseNet yielded the best results with a sensitivity of 87.91%±13.22 at a false negative rate of 1.26%±4.18.

Larsson, VeronicaKarolinska Inst, Dept Biosci & Nutr, Huddinge, Sweden (author)
Matuszewski, Damian J.Uppsala universitet,Avdelningen för visuell information och interaktion,Science for Life Laboratory, SciLifeLab,Bildanalys och människa-datorinteraktion,Centre for Image Analysis(Swepub:uu)damma800 (author)
Strömblad, StaffanKarolinska Inst, Dept Biosci & Nutr, Huddinge, Sweden (author)
Wählby, Carolina,professor,1974-Uppsala universitet,Science for Life Laboratory, SciLifeLab,Avdelningen för visuell information och interaktion,Bildanalys och människa-datorinteraktion,Centre for Image Analysis(Swepub:uu)cli05194 (author)
Uppsala universitetAvdelningen för visuell information och interaktion (creator_code:org_t)

In:2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI), s. 1626-162997815386933089781538693315

By the author/editor: Gupta, Anindya; Larsson, Veronic ...; Matuszewski, Dam ...; Strömblad, Staff ...; Wählby, Carolina ...

About the subject

MEDICAL AND HEALTH SCIENCES: MEDICAL AND HEAL ...; and Clinical Medicin ...; and Radiology Nuclea ...

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