Evaluation of model performance on the mammalian DeepCell dataset.

<p>(A) Cell-HOTA evaluated at various similarity thresholds α on the mammalian DeepCell dataset, using data from the test set. Five different algorithms are evaluated: Cell-TRACTR, DeLTA, EmbedTrack, Caliban, and Trackastra. (B) Cell-HOTA<sub>0.5</sub> results on the test set. (C)...

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محفوظ في:

التفاصيل البيبلوغرافية
المؤلف الرئيسي:	Owen M. O’Connor (11965460) (author)
مؤلفون آخرون:	Mary J. Dunlop (463579) (author)
منشور في:	2025
الموضوعات:	Biophysics Genetics Cancer Biological Sciences not elsewhere classified Information Systems not elsewhere classified track many objects present unique challenges global contextual dependencies existing architectures developed easily interpretable assessment defined microfluidic geometry convolutional neural networks bacteria growing within div >< p tr </ u r </ u c </ u division accuracy compared tracking cells without assess cell division cells </ p tractr (< u cell tracking based </ u division accuracy tracking cells cell tracking based models based architecture cell segmentation work establishes two dimensions tractr operates simultaneously segmenting results demonstrate new framework medical data fall short ecognition ), deep learning data analysis art algorithms analyzing biological
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Evaluation of model performance on the mammalian DeepCell dataset.

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