Comparison Between Various Color Spectra and Conventional Grayscale Imaging for Detection of Parenchymal Liver Lesions With B‐Mode Sonography

Merkel, Daniel R.; Brinkmann, Eckard; Kämmer, J.; Köhler, Miriam; Wiens, Daniel; Derwahl, Karl-Michael

doi:10.7863/ultra.15.14.08062

Cited by 8 publications

(12 citation statements)

References 11 publications

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“…Human perception of color change is limited and subjective, however, these factors can be eliminated by the suitable manipulation of a simple digital image. 23,24 An ordinary 8-bit RGB color digital image has more than 16 million possible colors and computer vision, which is the image data manipulation through an algorithm, has been successfully applied in several areas such as medical diagnosis, tra c control, facial recognition, autonomous cars, and others. 25,26 We hypothesized that digital image processing would be a sensitive and objective tool to identify color change in a reaction mixture.…”

Section: Resultsmentioning

confidence: 99%

Discovery of EDA-Complex Photocatalyzed Reactions Using Multidimensional Image Processing: Iminophosphorane Synthesis as a Case Study

Silva

Batista

Brocksom

et al. 2021

Preprint

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Herein, we report a multidimensional screening strategy for the discovery of EDA-complex photocatalyzed reactions using only photographic devices (webcam, cellphone) and TLC analysis. An algorithm was designed to identify automatically EDA-complex reactive mixtures in solution from digital image processing in a 96-wells microplate and by TLC-analysis. The code highlights the region of absorption of the mixture in the visible spectrum, and the quantity of the color change through grayscale values. Furthermore, the code identifies automatically the blurs on the TLC plate and classifies the mixture as colorimetric reactions, non-reactive or potentially reactive EDA mixtures. This strategy allowed us to discover and then optimize a new EDA-mediated approach for obtaining iminophosphoranes in up to 90% yield.

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Section: Resultsmentioning

confidence: 99%

Discovery of EDA-Complex Photocatalyzed Reactions Using Multidimensional Image Processing: Iminophosphorane Synthesis as a Case Study

Silva

Batista

Brocksom

et al. 2021

Preprint

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“…However, the advantage of B-mode colorization over gray mode imaging for the detection of focal liver lesions could not be proven (▶Fig. 10) [28].…”

Section: Chromatic Colorsmentioning

confidence: 99%

Ultrasound Image Optimization (“Knobology”): B-Mode

Zander

Hüske

Hoffmann

et al. 2020

Ultrasound Int Open

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Ultrasound is a ubiquitous and indispensable diagnostic and therapeutic tool in medicine. Due to modern equipment and automatic image optimization, the introduction of ultrasound imaging currently requires only little technical and physical knowledge. However, in-depth knowledge of the device functions and underlying mechanisms is essential for optimal image adjustment and documentation. From a medical as well as an aesthetic point of view, the goal should always be to achieve the best possible image quality. The first part of this article provides an overview of the handling of ultrasound systems, fundamental adjustments, and their optimization in B-mode ultrasound.

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“…The relation between these two parameters describes the direction angle θ of an imaginary vector that joins that pair of pixels. Considering that an image is usually represented as a matrix which rows are indicated by index i -which grows downwards-and which columns are indicated by index j -which grows rightwards-, the direction angle for a given pair of Offset parameters can be obtained by (9). This angle between a specific pair of pixels in the image is illustrated in Fig.…”

Section: C C C C C a A B A A A C B B A C A B C A C C C A B B C A Amentioning

confidence: 99%

“…In some applications [8], [9], [10] and [11] colored images have too much information that may not be very relevant for the desired application, so grayscale images can be used instead, reducing the amount of information to be processed and, by doing this, simplifying the following processing steps. For both colored and grayscale images, Haralick features -as will be shown later in this work-represent a good choice for texture extraction.…”

Section: Introductionmentioning

confidence: 99%

Texture Classification based on Spectral Analysis and Haralick Features

Valentin

Albuquerque

et al. 2016

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In this work we discuss a method to classify a set of texturized images based on the extraction of their Haralick Features. This kind of Classification is capable of providing texture-based measurements (such as contrast or correlation) and use them as main parameters to classify the same type of patterns in other images. In order to improve the classification success ratio a spectral analysis of the textures and, therefore, the use of filters, before the classification step, is proposed here. In this work the classification success has been evaluated using Mean and Canny filters. On the other hand, the Principal Component Analysis is used to optimize the features extracted for the patterns on each image, before introduced into the classifier. With this method the classifying success ratio for the KTH-TIPS subset and 10,000 different permutations was increased-in averagefrom 72.28% to 84.25%.

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Comparison Between Various Color Spectra and Conventional Grayscale Imaging for Detection of Parenchymal Liver Lesions With B‐Mode Sonography

Cited by 8 publications

References 11 publications

Discovery of EDA-Complex Photocatalyzed Reactions Using Multidimensional Image Processing: Iminophosphorane Synthesis as a Case Study

Discovery of EDA-Complex Photocatalyzed Reactions Using Multidimensional Image Processing: Iminophosphorane Synthesis as a Case Study

Ultrasound Image Optimization (“Knobology”): B-Mode

Texture Classification based on Spectral Analysis and Haralick Features

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