Improving Accuracy of Nuclei Segmentation by Reducing Histological Image Variability

Roohani, Yusuf; Kiss, Eric G.

doi:10.1007/978-3-030-00949-6_1

Cited by 2 publications

(1 citation statement)

References 11 publications

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“…For normalizing staining variations, there exist a multitude of algorithms. [100][101][102][103][104][105][106][107][108][109][110][111][112][113][114][115][116][117] These are based on histogram correction, deep learning and other methods. Algorithms also exist to digitally separate stains and even transfer them to a different set of stains.…”

Section: 21mentioning

confidence: 99%

Recent technical advances in whole slide imaging instrumentation

Katare

Gorthi

2021

Journal of Microscopy

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Microscopic observation of biological specimen smears is the mainstay of diagnostic pathology, as defined by the Digital Pathology Association. Though automated systems for this are commercially available, their bulky size and high cost renders them unusable for remote areas. The research community is investing much effort towards building equivalent but portable, low‐cost systems. An overview of such research is presented here, including a comparative analysis of recent reports. This paper also reviews recently reported systems for automated staining and smear formation, including microfluidic devices; and optical and computational automated microscopy systems including smartphone‐based devices. Image pre‐processing and analysis methods for automated diagnosis are also briefly discussed. It concludes with a set of foreseeable research directions that could lead to affordable, integrated and accurate whole slide imaging systems.

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Section: 21mentioning

confidence: 99%

Recent technical advances in whole slide imaging instrumentation

Katare

Gorthi

2021

Journal of Microscopy

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Scoping review on automatic color equalization algorithm

2021

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Digital image processing is at the base of everyday applications aiding humans in several fields, such as underwater monitoring, analysis of cultural heritage drawings, and medical imaging for computer-aided diagnosis. The starting point of all such application regards the image enhancement step. A desirable image enhancement step should simultaneously standardize the illumination in the image set, possibly removing bad or not-uniform illumination effects, and reveal all hidden details. In 2002, a successful perceptual image enhancement model, the automatic color equalization (ACE) algorithm, was proposed, which mimics the color and contrast adjustment of the human visual system (HVS). Given its widespread usage, its correlation with the HVS, and since it is easily implementable, we propose a scoping review to identify and classify the available evidence on ACE, starting from the papers citing the two funding papers on the algorithm. The aim of this work is the identification of what extent and in which ways ACE may have influenced the research in the color imaging field. Thanks to an accurate process of papers tagging, classification, and validation, we provide an overview of the main application domains in which ACE was successfully used and of the different ways in which this algorithm was implemented, modified, used, or compared.

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Improving Accuracy of Nuclei Segmentation by Reducing Histological Image Variability

Cited by 2 publications

References 11 publications

Recent technical advances in whole slide imaging instrumentation

Recent technical advances in whole slide imaging instrumentation

Scoping review on automatic color equalization algorithm

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