Multi-modal image sharpening in fourier transform infrared (FTIR) microscopy

Mankar, Rupali; Gajjela, Chalapathi Charan; Shahraki, Farideh Foroozandeh; Prasad, Saurabh; Mayerich, David; Reddy, Rohith

doi:10.1039/d1an00103e

Cited by 10 publications

(7 citation statements)

References 33 publications

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“…We mitigate annotation errors by limiting our labeling to unambiguous tissue areas and avoiding class boundaries. Furthermore, the alignment of images from adjacent sections is challenging, 69 and we obtained the best fit through manual adjustment. The five wavenumbers that we chose for O-PTIR imaging offer good classification performance, but optimizing the set of wavenumbers could lead to improved performance.…”

Section: Discussionmentioning

confidence: 99%

Leveraging mid-infrared spectroscopic imaging and deep learning for tissue subtype classification in ovarian cancer

Gajjela

Brun

Mankar

et al. 2023

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Section: Discussionmentioning

confidence: 99%

Leveraging mid-infrared spectroscopic imaging and deep learning for tissue subtype classification in ovarian cancer

Gajjela

Brun

Mankar

et al. 2023

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“…Mankar R., et al [8] introduced a Fourier Transform Infrared Technique (FTIR) for the multi-modal image sharpening. In this technique, curvelet-enabled multi-modal fusion approach was employed for fusing the spatial information in such a way that the spatial information from the dark-field images was fused into FTIR hyper spectral images.…”

Section: Other Pan Sharpening Techniquesmentioning

confidence: 99%

“…The newly designed technique in [6] failed to resolve the computational complexity issues. The developed approach in [8] failed to utilize data acquisition techniques for offering high resolution data with minimized computational time. In [10], the major challenge lies in utilizing different segmentation approaches for evaluating the injection coefficients.…”

Section: Research Gaps and Issuesmentioning

confidence: 99%

Study and Analysis of Various Pan-Sharpening Techniques: A Challenging Overview

Singh¹

2022

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Satellite sensors acquire massive data to exploit and address numerous human tasks. Due to the physical constraints, the usage of high spatial resolution multispectral (MS) images cannot be acquired by the unique devices. Hence, it is necessary to develop techniques by incorporating the images of MS and the panchromatic (PAN), also called Pan sharpening in remote sensing applications. Hence, this survey analyzes 30 research existing papers in Pan sharpening, which is based on various techniques, like neural network-based techniques, image fusion-based techniques, guided filterbased techniques, and optimization-based techniques. The analysis is based on the publication year of the research paper, research techniques employed, performance evaluation measures, and achievement of the research techniques. Also, the issues in the approaches are explained. Moreover, the future scope is to develop an efficient Pan sharpening technique based on the limitations recognized from the existing research Pan sharpening techniques.

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“…In addition, an unsupervised curvelet-based image fusion method effected fusing images of breast and ovarian tumour biopsies acquired from IR and dark-field microscopy. 16 In general, fusion algorithms differ in their performance and computational load. The most important difference between these fusion algorithms is in calculating the weight (i.e., balance the input of high-resolution and lowresolution image) which is established by solving an optimisation problem.…”

Section: Introductionmentioning

confidence: 99%