e-journal

Segmentation and Tracing of Single Neurons from 3D Confocal Microscope Images

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Abstract—In order to understand the brain, we need to first understand the morphology of neurons. In the neurobiology community, there have been recent pushes to analyze both neuron connectivity and the influence of structure on function. Currently, a technical roadblock that stands in the way of these studies is the inability to automatically trace neuronal structure from microscopy. On the image processing side, proposed tracing algorithms face difficulties in low contrast, indistinct boundaries, clutter, and complex branching structure. To tackle these difficulties, wedevelopTree2Tree,arobustautomaticneuronsegmentationand morphology generation algorithm. Tree2Tree uses a local medial tree generation strategy in combination with a global tree linking to build a maximum likelihood global tree. Recasting the neuron tracing problem in a graph-theoretic context enables Tree2Tree to estimate bifurcations naturally, which is currently a challenge for current neuron tracing algorithms. Tests on cluttered confocal microscopy images of Drosophila neurons give results that correspond to ground truth within a margin of ±2.75% normalized mean absolute error.

Index Terms—Neuron image analysis, neuron tracing, segmentation.

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Informasi Detail

Judul Seri

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No. Panggil

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Penerbit

: IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS., 2013

Deskripsi Fisik

IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS, VOL. 17, NO. 2, MARCH 2013 p. 319-335

Bahasa

English

ISBN/ISSN

2168-2194

Klasifikasi

NONE

Tipe Isi

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Tipe Media

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Tipe Pembawa

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Edisi

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Subjek

FOTOGRAFI KEDOKTERAN

Info Detail Spesifik

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Pernyataan Tanggungjawab

Saurav Basu ... [et al.]

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