Detection Microcalcification Mammograms Using by Jaganathan Subash (13 results)

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Taschenbuch. Condition: Neu. DETECTION OF MICROCALCIFICATION IN MAMMOGRAMS USING AI & ML TECHNIQUES | (A new modern Approach) | Subash Chandra Bose Jaganathan | Taschenbuch | Einband - flex.(Paperback) | Englisch | 2021 | LAP LAMBERT Academic Publishing | EAN 9786203471823 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.…

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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -One of the new modern and most efficient methods for breast cancer early detection is mammography. A new method for the detection and classification of microcalcifications is presented. It can be done in four stages: first, preprocessing stage deals with noise removal, and normalized the image. The second stage, Fuzzy c-Means clustering (FCM) is used for segmentation and pectoral muscle extraction using area calculation and finally microcalcifications detection. The third stage consists of two-dimensional discrete wavelet transforms are extracted from the detection of microcalcifications. And then, nine statistical features are calculated from the LL band of the wavelet transform. Finally, the extracted features are fed as input to the Artificial Neural Network and are classified into normal or abnormal (benign or malignant) images. The given classification approach is applied to a database of 322 dense mammographic images, originating from the MIAS database. The results are analyzed using MATLAB. 168 pp. Englisch.…

Condition: New. Print on Demand pp. 168.

Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Jaganathan Subash Chandra BoseDr. Subash Chandra Bose Jaganathan was working as an Electrical and Computer Engineering for more than 17 years in both industry and Teaching. He had been worked in international countries like KSA, Nort. …

Condition: New. PRINT ON DEMAND pp. 168.

Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - One of the new modern and most efficient methods for breast cancer early detection is mammography. A new method for the detection and classification of microcalcifications is presented. It can be done in four stages: first, preprocessing stage deals with noise removal, and normalized the image. The second stage, Fuzzy c-Means clustering (FCM) is used for segmentation and pectoral muscle extraction using area calculation and finally microcalcifications detection. The third stage consists of two-dimensional discrete wavelet transforms are extracted from the detection of microcalcifications. And then, nine statistical features are calculated from the LL band of the wavelet transform. Finally, the extracted features are fed as input to the Artificial Neural Network and are classified into normal or abnormal (benign or malignant) images. The given classification approach is applied to a database of 322 dense mammographic images, originating from the MIAS database. The results are analyzed using MATLAB.…

Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -One of the new modern and most efficient methods for breast cancer early detection is mammography. A new method for the detection and classification of microcalcifications is presented. It can be done in four stages: first, preprocessing stage deals with noise removal, and normalized the image. The second stage, Fuzzy c-Means clustering (FCM) is used for segmentation and pectoral muscle extraction using area calculation and finally microcalcifications detection. The third stage consists of two-dimensional discrete wavelet transforms are extracted from the detection of microcalcifications. And then, nine statistical features are calculated from the LL band of the wavelet transform. Finally, the extracted features are fed as input to the Artificial Neural Network and are classified into normal or abnormal (benign or malignant) images. The given classification approach is applied to a database of 322 dense mammographic images, originating from the MIAS database. The results are analyzed using MATLAB.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 168 pp. Englisch.…