Building a multispectral image dataset for colorectal tumor biopsy

Kunhoth, Suchithra; Al-Maadeed, Somaya

doi:10.1109/iwcmc.2017.7986548

Cited by 4 publications

(1 citation statement)

References 8 publications

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“…In addition to the studies presented before, there are other interesting and novel applications of pathological assistance using MSI/HSI. For example, authors in [86] collected MS images from four types of colorectal cells: viz. normal, hyperplastic polyps, tabular adenoma with low grade dysplasia and carcinoma.…”

Section: Hyperspectral Imaging In Gi Diagnosismentioning

confidence: 99%

Use of Hyperspectral/Multispectral Imaging in Gastroenterology. Shedding Some–Different–Light into the Dark

Ortega

Fabelo

Iakovidis

et al. 2019

JCM

105

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Hyperspectral/Multispectral imaging (HSI/MSI) technologies are able to sample from tens to hundreds of spectral channels within the electromagnetic spectrum, exceeding the capabilities of human vision. These spectral techniques are based on the principle that every material has a different response (reflection and absorption) to different wavelengths. Thereby, this technology facilitates the discrimination between different materials. HSI has demonstrated good discrimination capabilities for materials in fields, for instance, remote sensing, pollution monitoring, field surveillance, food quality, agriculture, astronomy, geological mapping, and currently, also in medicine. HSI technology allows tissue observation beyond the limitations of the human eye. Moreover, many researchers are using HSI as a new diagnosis tool to analyze optical properties of tissue. Recently, HSI has shown good performance in identifying human diseases in a non-invasive manner. In this paper, we show the potential use of these technologies in the medical domain, with emphasis in the current advances in gastroenterology. The main aim of this review is to provide an overview of contemporary concepts regarding HSI technology together with state-of-art systems and applications in gastroenterology. Finally, we discuss the current limitations and upcoming trends of HSI in gastroenterology.

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Section: Hyperspectral Imaging In Gi Diagnosismentioning

confidence: 99%

Use of Hyperspectral/Multispectral Imaging in Gastroenterology. Shedding Some–Different–Light into the Dark

Ortega

Fabelo

Iakovidis

et al. 2019

JCM

105

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A hierarchical algorithm with randomized learning for robust tissue segmentation and classification in digital pathology

Illarionova,

Hamoudi,

Zapevalina

et al. 2025

Information Sciences

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An Analytical Study on the Utility of RGB and Multispectral Imagery with Band Selection for Automated Tumor Grading

Kunhoth,

Al-Maadeed

2024

Diagnostics

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The implementation of tumor grading tasks with image processing and machine learning techniques has progressed immensely over the past several years. Multispectral imaging enabled us to capture the sample as a set of image bands corresponding to different wavelengths in the visible and infrared spectrums. The higher dimensional image data can be well exploited to deliver a range of discriminative features to support the tumor grading application. This paper compares the classification accuracy of RGB and multispectral images, using a case study on colorectal tumor grading with the QU-Al Ahli Dataset (dataset I). Rotation-invariant local phase quantization (LPQ) features with an SVM classifier resulted in 80% accuracy for the RGB images compared to 86% accuracy with the multispectral images in dataset I. However, the higher dimensionality elevates the processing time. We propose a band-selection strategy using mutual information between image bands. This process eliminates redundant bands and increases classification accuracy. The results show that our band-selection method provides better results than normal RGB and multispectral methods. The band-selection algorithm was also tested on another colorectal tumor dataset, the Texas University Dataset (dataset II), to further validate the results. The proposed method demonstrates an accuracy of more than 94% with 10 bands, compared to using the whole set of 16 multispectral bands. Our research emphasizes the advantages of multispectral imaging over the RGB imaging approach and proposes a band-selection method to address the higher computational demands of multispectral imaging.

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Building a multispectral image dataset for colorectal tumor biopsy

Cited by 4 publications

References 8 publications

Use of Hyperspectral/Multispectral Imaging in Gastroenterology. Shedding Some–Different–Light into the Dark

Use of Hyperspectral/Multispectral Imaging in Gastroenterology. Shedding Some–Different–Light into the Dark

A hierarchical algorithm with randomized learning for robust tissue segmentation and classification in digital pathology

An Analytical Study on the Utility of RGB and Multispectral Imagery with Band Selection for Automated Tumor Grading

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