A Survey of Noise Removal Methodologies for Lung Cancer Diagnosis

Saini, Ashwini Kumar; Bhadauria, H.S.; Singh, Annapurna

doi:10.1109/cict.2016.139

Cited by 4 publications

(6 citation statements)

References 11 publications

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“…In medical applications, the probability of noise creation is increased because of the fast scanning process . Different types of noises in medical imaging instruments, such as impulse, Gaussian, and speckle can be created during image capture or transmission . Numerous research works have been conducted in detection and elimination of noise in medical images.…”

Section: Introductionmentioning

confidence: 99%

“…Sawant et al designed an adaptive median filter for removal of impulse noise in X‐ray images and speckle noise in ultrasound images . In the study of Saini et al, medical images, which are used for detecting cancer in different parts of human body, are considered and different types of noise affecting such images are reviewed. Impulse noise is investigated in many different medical imaging applications such as MR imaging and mammogram images …”

Section: Introductionmentioning

confidence: 99%

“…In [3] an adaptive median filter for removal of impulse noise in X-ray images and speckle noise in ultrasound images is proposed. In [4] medical images which are used for detecting cancer in different parts of human body are considered and different types of noise effecting such images are reviewed.…”

Section: Introductionmentioning

confidence: 99%

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Real‐time removal of impulse noise from MR images for radiosurgery applications

HosseinKhani

Hajabdollahi

Karimi

et al. 2019

Circuit Theory & Apps

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Summary In the recent years, image processing techniques are used as a tool to improve detection and diagnostic capabilities in the medical applications. Among these techniques, medical image enhancement algorithms play an essential role in the removal of the noise, which can be produced by medical instruments and during image transfer. Impulse noise is a major type of noise, which is produced by medical imaging systems, such as MRI, computed tomography (CT), and angiography instruments. An embeddable hardware module, which can denoise medical images before and during surgical operations, could be very helpful. In this paper, an accurate algorithm is proposed for real‐time removal of impulse noise in medical images. Our algorithm categorizes all image blocks into three types of edge, smooth, and disordered areas. A different reconstruction method is applied to each category of blocks for noise removal. The proposed method is tested on MR images. Simulation results show acceptable denoising accuracy for various levels of noise. Also, an field programmable gate array (FPGA) implementation of our denoising algorithm shows acceptable hardware resource utilization. Hence, the algorithm is suitable for embedding in medical hardware instruments such as radiosurgery devices.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Real‐time removal of impulse noise from MR images for radiosurgery applications

HosseinKhani

Hajabdollahi

Karimi

et al. 2019

Circuit Theory & Apps

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“…Devices and applications of computer produced driven by the innovation in technology have rearranged the operation which consists of images those involved more relevant ideas about these issues [1]. Past decades many researchers have been directed to multiple directions for profiting from the techniques of image processing in our daily life.…”

Section: Introductionmentioning

confidence: 99%

“…Such as impulse noise can appear in images during acquisition, storage, or transmission which can latterly affect stage of processing image may not remove properly during preserving the details. This problem rises in many fields such as medical imaging [3], and the analysis of satellite images, there are different types of noise models which include thermal noise, RF noise, Gaussian noise, salt and pepper noise, speckle noise and Brownian noise [1,4].…”

Section: Introductionmentioning

confidence: 99%

Improved Gaussian Filtering Model for Highly Noised Image by Salt and Pepper

Khuhro¹,

Dong-jun²,

Huang³

et al. 2017

dtcse

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Abstract. Image denoising is one of the most significant areas within digital image processing. Such as impulse noise can appear in images during acquisition, storage, or transmission which can latterly affect stage of processing image, and may not remove properly during preserving the details of effected image. After reviewing the different techniques, in this paper, we have proposed a significant algorithm which does detect and reduce the level of salt and pepper noise in less computation time and techniques.

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