Feed forwarded CT image registration for tumour and cyst detection using rigid transformation with HSV colour segmentation

Barik, Prabhat Kumar; Barik, Ram Chandra

doi:10.1504/ijcsyse.2019.10025328

Cited by 2 publications

(2 citation statements)

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“…So, all kinds of data including images need to be processed before feeding it to the ML model. The collected images are normally messy and are gathered from different sources [5]. So, the images need to be standardized and cleaned up.…”

Section: Pre-processing Imagementioning

confidence: 99%

A Skin Cancer Image Detection Interface Tool Using VLF Support Vector Machine Classification

Mishra¹,

Meher²,

Kustha³

et al. 2021

Advances in Intelligent Systems and Computing

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As per WHO, in most cases, early diagnosis and screening of cancer increase the chances for successful treatment by focusing on indicative of patients as rapidly as possible. The medical diagnosis process is playing a significant role in the automatic analysis of the image and evaluation of the skin cancer, but in some ways, it gets detrimental and pain also. Keeping the last point in mind, we proposed a method for the analysis of image to determine whether it is skin cancer or not. The machine learning characteristic is to be considered as prospect theory, decision models that exhibited new data, and they are capable of adapting different conditions independently. Various methods have been proposed to deal with skin cancer disease. As cancer exists in different stages, premature diagnosis is necessary for a patient to control cancer at early stages. The steps that are included in this study are collecting the skin cancer image, processing by some skin cancer parameters. The tools that we have used to detect data from different skin cancers images include principal component technology, which reduce the high-dimensional image into small dimension and after that applied to enhance clustering of the data, which is the most important method of unsupervised learning. This chapter draws a novel hybrid statistical feature extraction by using GLCM and PCA technology and statistical dimension reduction scheme with fuzzy C-mean novel clustering. The main gist of evolving this paper is to extract the people to the deleterious diagnostic test technique and easily identify the cancer patients through this entire process of SVM classification algorithm with suitable appropriate results, in some pandemic position. The results of the proposed scheme give better performance in contrast with the existing popular methods.

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Section: Pre-processing Imagementioning

confidence: 99%

A Skin Cancer Image Detection Interface Tool Using VLF Support Vector Machine Classification

Mishra¹,

Meher²,

Kustha³

et al. 2021

Advances in Intelligent Systems and Computing

View full text Add to dashboard Cite

show abstract

“…The points at which the image brightness adjustment occurs rapidly are usually furnished in a set of edges of curved line segments. Originally edge detection is a derivative-based method that is classified into first-order and second-order derivative filters [5][6][7][8][9][10][11][12]. Firstorder derivative-based filters work better with thick edges while second-order ones give better results with thinner or finer edges.…”

Section: Edge Detectionmentioning

confidence: 99%

Forgery Detection of Fake Currency Using Image Derivative Based Segmentation Technique

Mishra¹,

Patel²,

Bano³

et al. 2020

IJEAST

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Fake currency is a threat to each country throughout the globe. This paper is centered to detect the fake currency use of the image segmentation technique. Fake foreign money aims in discovering the forgery currency. The first step in image processing is preprocessing of the image involve containing cropping smoothing and adjustment of the image. The second step contains the conversion of the image into a gray coloration image. The conversion is done after image segmentation. The features include removal and mitigation. In the last step, compare the image to the original or the forgery image. India is more vulnerable to this problem which is results in a big hurdle. The empirical simulation is carried out using Rupees 100, 500 note of Indian Currency.

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Feed forwarded CT image registration for tumour and cyst detection using rigid transformation with HSV colour segmentation

Cited by 2 publications

References 0 publications

A Skin Cancer Image Detection Interface Tool Using VLF Support Vector Machine Classification

A Skin Cancer Image Detection Interface Tool Using VLF Support Vector Machine Classification

Forgery Detection of Fake Currency Using Image Derivative Based Segmentation Technique

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