An Intelligent Recurrent Neural Network with Long Short-Term Memory (LSTM) BASED Batch Normalization for Medical Image Denoising.
The process of denoising of medical images that are corrupted by noise is considered as a long established setback in the signal or image processing domain. An effective system for denoising in order to remove white, salt and also pepper noises by means of merging the Long Short-Term Memory, otherwi...
| Publicado en: | Journal of Medical Systems Vol. 43; no. 8 |
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| Autores principales: | , , |
| Formato: | diagnostic images equations & formulas research tables/charts Journal Article |
| Publicado: |
Springer Nature
Aug2019
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=137490032&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 137490032 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01485598 4N0 jtl: Journal of Medical Systems issn: 01485598 maglogo: N pubinfo: dt: Aug2019 vid: 43 iid: 8 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 137490032 137490032 137490032 10.1007/s10916-019-1371-9 137490032 ppct: 1 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: An Intelligent Recurrent Neural Network with Long Short-Term Memory (LSTM) BASED Batch Normalization for Medical Image Denoising. aug: au: Rajeev, R. Samath, J. Abdul Karthikeyan, N. K. affil: Department of Information Technology, Sri Ramakrishna College of Arts and Science (Formerly SNR Sons College), Coimbatore, Tamil Nadu, India sug: subj: Recurrent Neural Networks Image Processing, Computer Assisted Signal Processing, Computer Assisted Long Short-Term Memory Algorithms Tomography, X-Ray Computed Noise Artificial Intelligence ab: The process of denoising of medical images that are corrupted by noise is considered as a long established setback in the signal or image processing domain. An effective system for denoising in order to remove white, salt and also pepper noises by means of merging the Long Short-Term Memory, otherwise known as LSTM, based Batch Normalization and Recurrent Neural Network or RNN techniques have been proposed in this research paper. The images of the lung CT are considered as an input in this particular work. Following this, an effectual batch size is calculated by employing the method of Particle Swarm Optimization (PSO). To denoise the image, Recurrent Neural Network or RNN algorithm were proposed, here to reduce the internal covariate shift present in the neural networks, the Long Short-Term Memory or LSTM based Batch Normalization is brought-in. With respect to SNR or Peak Signal to Noise Ratio and Mean Square Error (MSE), operations were assessed. This algorithm is considered as competitive to other denoising schemes which have been confirmed by the experimental outcomes. pubtype: Academic Journal doctype: diagnostic images equations & formulas research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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