Adaptive Histogram Equalization For Automatic Contrast Enhancement Of Medical Images

Pizer, Stephen M.; Austin, John D.; Perry, John; Safrit, Hal D.; Zimmerman, John B.

doi:10.1117/12.975399

Cited by 35 publications

(7 citation statements)

References 2 publications

(1 reference statement)

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“…As an improvement to histogram equilibration (HE) and adaptive histogram equilibration (AHE), in CLAHE an adjustable threshold limits the maximal amount of contrast enhancement in order to avoid the over amplification of noise 46 . CLAHE is also applied for enhancing the contrast of sonographies, CT and MRI data 62 , 63 .…”

Section: Methodsmentioning

confidence: 99%

3D histopathology of human tumours by fast clearing and ultramicroscopy

Sabdyusheva-Litschauer

Becker

Saghafi

et al. 2020

Sci Rep

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Here, we describe a novel approach that allows pathologists to three-dimensionally analyse malignant tissues, including the tumour-host tissue interface. Our visualization technique utilizes a combination of ultrafast chemical tissue clearing and light-sheet microscopy to obtain virtual slices and 3D reconstructions of up to multiple centimetre sized tumour resectates. For the clearing of tumours we propose a preparation technique comprising three steps: (a) Fixation and enhancement of tissue autofluorescence with formalin/5-sulfosalicylic acid. (b) Ultrafast active chemical dehydration with 2,2-dimethoxypropane and (c) refractive index matching with dibenzyl ether at up to 56 °C. After clearing, the tumour resectates are imaged. The images are computationally post-processed for contrast enhancement and artefact removal and then 3D reconstructed. Importantly, the sequence a–c is fully reversible, allowing the morphological correlation of one and the same histological structures, once visualized with our novel technique and once visualized by standard H&E- and IHC-staining. After reverting the clearing procedure followed by standard H&E processing, the hallmarks of ductal carcinoma in situ (DCIS) found in the cleared samples could be successfully correlated with the corresponding structures present in H&E and IHC staining. Since the imaging of several thousands of optical sections is a fast process, it is possible to analyse a larger part of the tumour than by mechanical slicing. As this also adds further information about the 3D structure of malignancies, we expect that our technology will become a valuable addition for histological diagnosis in clinical pathology.

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Section: Methodsmentioning

confidence: 99%

3D histopathology of human tumours by fast clearing and ultramicroscopy

Sabdyusheva-Litschauer

Becker

Saghafi

et al. 2020

Sci Rep

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“…Adaptive histogram equalisation (AHE) and contrast limited adaptive histogram equalisation (CLAHE) extend HE and are are discussed in detail in Section III. CLAHE was first applied as a enhancement technique for low contrast-medical imagery [15] and it is based on the principle of HE. Histogram Specification (HS) techniques map the intensity distributions to the desired shape and are commonly used for contrast enhancement of medical and feature-poor imagery [9] [15] [16].…”

Section: B Image Enhancementmentioning

confidence: 99%

Saliency Improvement in Feature-Poor Surgical Environments Using Local Laplacian of Specified Histograms

et al. 2020

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Navigation in endoscopic environments requires an accurate and robust localisation system. A key challenge in such environments is the paucity of visual features that hinders accurate tracking. This paper examines the performance of three image enhancement techniques for tracking under such feature-poor conditions including Contrast Limited Adaptive Histogram Specification (CLAHS), Fast Local Laplacian Filtering (LLAP) and a new combination of the two coined Local Laplacian of Specified Histograms (LLSH). Two cadaveric knee arthroscopic datasets and an underwater seabed inspection dataset are used for the analysis, where results are interpreted by defining visual saliency as the number of correctly matched key-point (SIFT and SURF) features. Experimental results show a significant improvement in contrast quality and feature matching performance when image enhancement techniques are used. Results also demonstrate the LLSHs ability to vastly improve SURF tracking performance indicating more than 87% of successfully matched frames. A comparative analysis provides some important insights useful in the design of vision-based navigation for autonomous agents in feature-poor environments.

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“…8. 22,23 However, this algorithm can amplify some noisy components during image enhancement. In order to control …”

Section: -5mentioning

confidence: 99%

Deep tissue near-infrared imaging for vascular network analysis

Seker

Engin

2017

J. Innov. Opt. Health Sci.

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Subcutaneous vein network plays important roles to maintain microcirculation that is related to some diagnostic aspects. Despite developments of optical imaging technologies, still the di±culties about deep skin vascular imaging have been continued. On the other hand, since hemoglobin concentration of human blood has key role in the veins imaging by optical manner, the used wavelength in vascular imaging, must be chosen considering absorption of hemoglobin. In this research, we constructed a near infrared (NIR) light source because of lower absorption of hemoglobin in this optical region. To obtain vascular image, re°ectance geometry was used. Next, from recorded images, vascular network analysis, such as calculation of width of vascular of interest and complexity of selected region were implemented. By comparing with other modalities, we observed that proposed imaging system has great advantages including nonionized radiation, moderate penetration depth of 0.5-3 mm and diameter of 1 mm, cost-e®ective and algorithmic simplicity for analysis.Keywords: Vascular NIR imaging; manufacturing liquid and solid phantoms; di®use optical imaging; image processing and analysis; optical imaging system design.

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Adaptive Histogram Equalization For Automatic Contrast Enhancement Of Medical Images

Cited by 35 publications

References 2 publications

3D histopathology of human tumours by fast clearing and ultramicroscopy

3D histopathology of human tumours by fast clearing and ultramicroscopy

Saliency Improvement in Feature-Poor Surgical Environments Using Local Laplacian of Specified Histograms

Deep tissue near-infrared imaging for vascular network analysis

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