A Proposed HSV-Based Pseudo Coloring Scheme for Enhancing Medical Image

Semary, Noura A.

doi:10.5121/csit.2018.80407

Cited by 7 publications

(9 citation statements)

References 10 publications

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“…In this work, implementation of every stage of the algorithm listed in section.5 to provide the x-ray images with artificial colors specific colour or mixture of colors using sub equations composite from equation (1) by changing both trigonometric functions and mathematical operations. This sort of change has a wide impact on the output images.…”

Section: The Framework and Experimental Resultsmentioning

confidence: 99%

“…Medical images have a significant function in detecting and diagnosing diseases in the human body and living organisms in various medical fields, and they are able to examine complicated and sophisticated interior biological processes [1]. add to that it contains priceless anatomical information about clinical procedures [2].The most prominent types in the medical images are x-ray, ultrasound, magnetic resonance imaging (MRI) and computed tomography, magnetic resonance imaging(MRI), all those types usually come in grayscale which has only 256 gray shades variations, in other words, the color information has been overlooked in medical image analysis applications, this is because they are monochrome imaging models, and since colour is a powerful tool to increase the quality of information display [3] [4], therefore, the researchers had to utilized the colorization technology [5].…”

Section: Introductionmentioning

confidence: 99%

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Frontal Chest X-Ray Image Colorization Using Various Mathematical Experimental Equations

Al-khafaji¹,

Al-Yasiri²

2019

JK-Physics

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Chest x-ray medical images are widely used for diagnostic purposes for several reasons including it available, attainable and excellent imaging of hard tissues like bones, but there is difficulty in imaging of the soft tissues, moreover the saturated colour of the x-ray image causing intricacy to read it, therefore, turned attention to the colorization process which can be used to transform the grayscale medical images to the colour medical images. In this paper, a new pseudo-coloring method proposed for colorizing the frontal chest x-ray medical images which are very important for disease detection and recognition. The key idea of this method is applying different and various experimental mathematical equations on the proposed medical sample image, which it belongs to the patient with Hydatid cyst parasite disease in the lung. The counterfeit coloring had intense contribute in enhancing of the visual attractiveness of medical images, the output colored images have a better visual description, it has a possibility to describe hidden information better than a conventional monochromatic image, this is an excellent indicator of the algorithm's suitability for the purpose for which it was formulated.

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Section: The Framework and Experimental Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Frontal Chest X-Ray Image Colorization Using Various Mathematical Experimental Equations

Al-khafaji¹,

Al-Yasiri²

2019

JK-Physics

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“…Adding semantic segmentation can effectively avoid the content-mismatch problem and improve the color result (3). The total structural loss used by Luan et al [25] is (5). The regularization term can not make human eye to find the loss of its details, but the details still have some losses which seen by the objective evaluation index (SSIM) (in Table 1).…”

Section: B Deep Learning-based Methodsmentioning

confidence: 99%

“…The color medical image can simulate the visual efferent of optical endoscope, and increase the intuitive feeling of virtual observation, which is conducive to the correct judgment of observation [3]. It has been proved by clinical practice practice that pseudo-color images can highlight the details of organs and tissues better comparing with gray images [4], which can help doctors make correct judgment and avoid misjudgment [5], and also help for medical image segmentation [2], such as the color medical image in Fig. 1 can easily distinguish to the chest and lungs, glioma center, brain and bone.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Medical Image Deep Color Perception Algorithm

Zeng

Tong

et al. 2020

IEEE Access

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The existing medical imaging technologies have little consideration on color information, thus most of medical images are gray. Classical hand-craft features-based methods have obtained unsatisfactory results in colorizing medical images. Moreover, these methods ignore the deep feature of medical images that represent pathology and color information. In this paper, we propose a novel method that iteratively colorizes grayscale medical images under preserving content in fine-tuned deep neural network. To the best of our knowledge, there is no currently work that attempts to colorize the medical image by using deep neural network. Specifically, we propose Y-loss which is defined as nonlinear combination of 1 and 2 norm to preserve content invariance between target and colorized medical image. Then, adaptive reference image search algorithm is introduced to code reference and target medical image with D-hash and search reference image in hash code automatically, which free the manual selection of the reference image. Extensive experiment results show that the proposed method can generate higher quality colored medical image than recent state-of-the-art methods, and can be approved by the doctor. The objective evaluation (PSNR and SSIM) outperform an average increment 24% and 47% than baseline method, respectively. Our code is available at: https://github.com/Tongshiyue/Adaptive-medical-image-deep-color-perception-algorithm. INDEX TERMS Medical images enhance, color images, color transfer, deep neural network, automatic search.

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“…A useful technique is pseudo-colouring, which encodes continuously varying values using a sequence of colours [55]. It has been widely used to support diagnosis from medical images, including breast disease [58], and for highlighting details in organs and bones structures that would otherwise be difficult to perceive [59,61]. It is also used extensively in geographic and time series visualisations, where applications include encoding elevation in the data or showing changes over time [55,60].…”

Section: Plos Onementioning

confidence: 99%

Pseudo-colouring an ECG enables lay people to detect QT-interval prolongation regardless of heart rate

et al. 2020

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Drug-induced long QT syndrome (diLQTS), characterized by a prolongation of the QT-interval on the electrocardiogram (ECG), is a serious adverse drug reaction that can cause the life-threatening arrhythmia Torsade de Points (TdP). Self-monitoring for diLQTS could therefore save lives, but detecting it on the ECG is difficult, particularly at high and low heart rates. In this paper, we evaluate whether using a pseudo-colouring visualisation technique and changing the coordinate system (Cartesian vs. Polar) can support lay people in identifying QT-prolongation at varying heart rates. Four visualisation techniques were evaluated using a counterbalanced repeated measures design including Cartesian no-colouring, Cartesian pseudo-colouring, Polar no-colouring and Polar pseudo-colouring. We used a multireader, multi-case (MRMC) receiver operating characteristic (ROC) study design within a psychophysical paradigm, along with eye-tracking technology. Forty-three lay participants read forty ECGs (TdP risk n = 20, no risk n = 20), classifying each QT-interval as normal/ abnormal, and rating their confidence on a 6-point scale. The results show that introducing pseudo-colouring to the ECG significantly increased accurate detection of QT-interval prolongation regardless of heart rate, T-wave morphology and coordinate system. Pseudocolour also helped to reduce reaction times and increased satisfaction when reading the ECGs. Eye movement analysis indicated that pseudo-colour helped to focus visual attention on the areas of the ECG crucial to detecting QT-prolongation. The study indicates that pseudo-colouring enables lay people to visually identify drug-induced QT-prolongation regardless of heart rate, with implications for the more rapid identification and management of diLQTS.

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A Proposed HSV-Based Pseudo Coloring Scheme for Enhancing Medical Image

Abstract: Medical imaging is one of the most attractive topics of image processing and understanding

Cited by 7 publications

References 10 publications

Frontal Chest X-Ray Image Colorization Using Various Mathematical Experimental Equations

Frontal Chest X-Ray Image Colorization Using Various Mathematical Experimental Equations

Adaptive Medical Image Deep Color Perception Algorithm

Pseudo-colouring an ECG enables lay people to detect QT-interval prolongation regardless of heart rate

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