Plankton reconstruction through robust statistical optical tomography

Roi Ronen; Yacov Attias; Yoav Y. Schechner; Jules S. Jaffe; Eric Orenstein

doi:https://doi.org/10.1364/JOSAA.423037

Plankton reconstruction through robust statistical optical tomography

Roi Ronen, Yacov Attias, Yoav Y. Schechner, Jules S. Jaffe, Eric Orenstein

Technion - Israel Institute of Technology

Research output: Contribution to journal › Article › peer-review

Abstract

Plankton interact with the environment according to their size and three-dimensional (3D) structure. To study them outdoors, these translucent specimens are imaged in situ. Light projects through a specimen in each image. The specimen has a random scale, drawn from the population’s size distribution and random unknown pose. The specimen appears only once before drifting away. We achieve 3D tomography using such a random ensemble to statistically estimate an average volumetric distribution of the plankton type and specimen size. To counter errors due to non-rigid deformations, we weight the data, drawing from advanced models developed for cryo-electron microscopy. The weights convey the confidence in the quality of each datum.

error model. We demonstrate the approach on live plankton using an underwater field microscope.

Original language	English
Pages (from-to)	1320-1331
Number of pages	12
Journal	Journal of the Optical Society of America A: Optics and Image Science, and Vision
Volume	38
Issue number	9
DOIs	https://doi.org/10.1364/JOSAA.423037
State	Published - Sep 2021

All Science Journal Classification (ASJC) codes

Electronic, Optical and Magnetic Materials
Atomic and Molecular Physics, and Optics
Computer Vision and Pattern Recognition

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https://doi.org/10.1364/JOSAA.423037

Cite this

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title = "Plankton reconstruction through robust statistical optical tomography",

abstract = "Plankton interact with the environment according to their size and three-dimensional (3D) structure. To study them outdoors, these translucent specimens are imaged in situ. Light projects through a specimen in each image. The specimen has a random scale, drawn from the population{\textquoteright}s size distribution and random unknown pose. The specimen appears only once before drifting away. We achieve 3D tomography using such a random ensemble to statistically estimate an average volumetric distribution of the plankton type and specimen size. To counter errors due to non-rigid deformations, we weight the data, drawing from advanced models developed for cryo-electron microscopy. The weights convey the confidence in the quality of each datum.error model. We demonstrate the approach on live plankton using an underwater field microscope.",

author = "Roi Ronen and Yacov Attias and Schechner, {Yoav Y.} and Jaffe, {Jules S.} and Eric Orenstein",

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TY - JOUR

T1 - Plankton reconstruction through robust statistical optical tomography

AU - Ronen, Roi

AU - Attias, Yacov

AU - Schechner, Yoav Y.

AU - Jaffe, Jules S.

AU - Orenstein, Eric

PY - 2021/9

Y1 - 2021/9

N2 - Plankton interact with the environment according to their size and three-dimensional (3D) structure. To study them outdoors, these translucent specimens are imaged in situ. Light projects through a specimen in each image. The specimen has a random scale, drawn from the population’s size distribution and random unknown pose. The specimen appears only once before drifting away. We achieve 3D tomography using such a random ensemble to statistically estimate an average volumetric distribution of the plankton type and specimen size. To counter errors due to non-rigid deformations, we weight the data, drawing from advanced models developed for cryo-electron microscopy. The weights convey the confidence in the quality of each datum.error model. We demonstrate the approach on live plankton using an underwater field microscope.

AB - Plankton interact with the environment according to their size and three-dimensional (3D) structure. To study them outdoors, these translucent specimens are imaged in situ. Light projects through a specimen in each image. The specimen has a random scale, drawn from the population’s size distribution and random unknown pose. The specimen appears only once before drifting away. We achieve 3D tomography using such a random ensemble to statistically estimate an average volumetric distribution of the plankton type and specimen size. To counter errors due to non-rigid deformations, we weight the data, drawing from advanced models developed for cryo-electron microscopy. The weights convey the confidence in the quality of each datum.error model. We demonstrate the approach on live plankton using an underwater field microscope.

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U2 - https://doi.org/10.1364/JOSAA.423037

DO - https://doi.org/10.1364/JOSAA.423037

M3 - مقالة

SN - 1084-7529

VL - 38

SP - 1320

EP - 1331

JO - Journal of the Optical Society of America A: Optics and Image Science, and Vision

JF - Journal of the Optical Society of America A: Optics and Image Science, and Vision

IS - 9

ER -

Plankton reconstruction through robust statistical optical tomography

Abstract

All Science Journal Classification (ASJC) codes

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