Dye Amount Estimation in a Papanicolaou-stained specimen using Multispectral Imaging

Papanicolaou stain is mainly used in cytological diagnosis such as gynecological diseases. In the image analysis of stained histopathology specimens, color unmixing technique, which estimates the dye abundance map, is useful. In this paper, we apply the dye amount estimation method based on color unmixing to Papanicolaou-stained specimen. In the proposed method, we capture the Papanicolaou-stained samples using a multispectral microscope, and then we estimate the amount of dyes from the observation and practically measured the spectral characteristics of the stain. Besides, we construct an application depicting the amount of stain and the bar-graph plot. In the experiments, we verify the feasibility of the proposed method and analyze a precancerous lesion of the uterine cervix using the proposed method.

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Quantitative Image Analysis of Nuclear Chromatin Distribution for Cytological Diagnosis

Acta Cytologica ◽

10.1159/000330672 ◽

2011 ◽

Vol 55 (5) ◽

pp. 455-459 ◽

Cited By ~ 5

Author(s):

Ryotaro Jingu ◽

Masafumi Ohki ◽

Sumiko Watanabe ◽

Sadafumi Tamiya ◽

Setsuo Sugishima ◽

...

Keyword(s):

Image Analysis ◽

Quantitative Image Analysis ◽

Cytological Diagnosis ◽

Nuclear Chromatin ◽

Quantitative Image

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A predictive and parametrized architecture for image analysis algorithm implementations on FPGA adapted to multispectral imaging

2008 First Workshops on Image Processing Theory, Tools and Applications ◽

10.1109/ipta.2008.4743765 ◽

2008 ◽

Cited By ~ 1

Author(s):

Junyan Tan ◽

Linlin Zhang ◽

Virginie Fresse ◽

Anne Claire Legrand ◽

Dominique Houzet

Keyword(s):

Image Analysis ◽

Multispectral Imaging ◽

Analysis Algorithm ◽

Image Analysis Algorithm

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Estimation Method of Fluorescent Donaldson Matrices Based on Multispectral Imaging Data

Color and Imaging Conference ◽

10.2352/issn.2169-2629.2020.28.36 ◽

2020 ◽

Vol 2020 (28) ◽

pp. 227-231

Author(s):

Shoji Tominaga

Keyword(s):

Reliable Method ◽

Multispectral Imaging ◽

Estimation Method ◽

Visible Range ◽

Multiple Response ◽

Imaging Data ◽

Object Surface ◽

Spectral Functions ◽

Simulation Experiments ◽

Image Acquisition System

This paper proposes a compact and reliable method to estimate the bispectral Donaldson matrices of fluorescent objects by using multispectral imaging data. We suppose that an image acquisition system allows multiple illuminant projections to the object surface and multiple response channels in the visible range. The Donaldson matrix is modeled as a twodimensional array with the excitation range (350, 700 nm) and the reflection and emission ranges (400, 700 nm). The observation model is described using the spectral sensitivities of a camera and the spectral functions of reflectance, emission, and excitation. The problem of estimating the spectral functions is formulated as a least squares problem to minimize the residual error of the observations and the roughness of the spectral functions. An iterative algorithm is developed to obtain the optimal estimates of the whole spectral functions. The performance of the proposed method is examined in simulation experiments using multispectral imaging data in detail.

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Abstract 1141: Quantitating signaling pathway proteins in FFPE sections using multispectral imaging and automated image analysis

10.1158/1538-7445.am10-1141 ◽

2010 ◽

Author(s):

Clifford Hoyt ◽

Kristin Lane ◽

Humphrey Gardner ◽

Michael Feldman

Keyword(s):

Image Analysis ◽

Signaling Pathway ◽

Multispectral Imaging ◽

Automated Image Analysis

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Landslide mapping with multi-scale object-based image analysis – a case study in the Baichi watershed, Taiwan

Natural Hazards and Earth System Science ◽

10.5194/nhess-11-2715-2011 ◽

2011 ◽

Vol 11 (10) ◽

pp. 2715-2726 ◽

Cited By ~ 41

Author(s):

T. Lahousse ◽

K. T. Chang ◽

Y. H. Lin

Keyword(s):

Image Analysis ◽

Spectral Characteristics ◽

Satellite Image ◽

Shallow Landslides ◽

Training Dataset ◽

Validation Dataset ◽

Spectral Difference ◽

Multi Scale ◽

Object Based Image Analysis ◽

Object Based

Abstract. We developed a multi-scale OBIA (object-based image analysis) landslide detection technique to map shallow landslides in the Baichi watershed, Taiwan, after the 2004 Typhoon Aere event. Our semi-automated detection method selected multiple scales through landslide size statistics analysis for successive classification rounds. The detection performance achieved a modified success rate (MSR) of 86.5% with the training dataset and 86% with the validation dataset. This performance level was due to the multi-scale aspect of our methodology, as the MSR for single scale classification was substantially lower, even after spectral difference segmentation, with a maximum of 74%. Our multi-scale technique was capable of detecting landslides of varying sizes, including very small landslides, up to 95 m2. The method presented certain limitations: the thresholds we established for classification were specific to the study area, to the landslide type in the study area, and to the spectral characteristics of the satellite image. Because updating site-specific and image-specific classification thresholds is easy with OBIA software, our multi-scale technique is expected to be useful for mapping shallow landslides at watershed level.

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