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A 3D reconstruction of pulmonary nodules from 2D CT images computer aided diagnosis based system / (Record no. 83323)

MARC details
000 -LEADER
fixed length control field 02187cam a2200313 a 4500
003 - CONTROL NUMBER IDENTIFIER
control field EG-GiCUC
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 211128s2021 ua dh f m 000 0 eng d
040 ## - CATALOGING SOURCE
Original cataloging agency EG-GiCUC
Language of cataloging eng
Transcribing agency EG-GiCUC
041 0# - LANGUAGE CODE
Language code of text/sound track or separate title eng
049 ## - LOCAL HOLDINGS (OCLC)
Holding library Deposite
097 ## - Thesis Degree
Thesis Level Ph.D
099 ## - LOCAL FREE-TEXT CALL NUMBER (OCLC)
Classification number Cai01.13.03.Ph.D.2021.Ay.A
100 0# - MAIN ENTRY--PERSONAL NAME
Personal name Ayat Motawakkel Karrar Ahmed
245 12 - TITLE STATEMENT
Title A 3D reconstruction of pulmonary nodules from 2D CT images computer aided diagnosis based system /
Statement of responsibility, etc. Ayat Motawakkel Karrar Ahmed ; Supervised Manal Abdelwahed , Mai Said Mabrouk
246 15 - VARYING FORM OF TITLE
Title proper/short title بناء أورام الرئة ثلاثية الأبعاد من الصور المقطعية ثنائية الأبعاد اعتمادا على نظام تشخيص الحاسب الآلى
260 ## - PUBLICATION, DISTRIBUTION, ETC.
Place of publication, distribution, etc. Cairo :
Name of publisher, distributor, etc. Ayat Motawakkel Karrar Ahmed ,
Date of publication, distribution, etc. 2021
300 ## - PHYSICAL DESCRIPTION
Extent 102 P. :
Other physical details charts , facsimiles ;
Dimensions 30cm
502 ## - DISSERTATION NOTE
Dissertation note Thesis (Ph.D.) - Cairo University - Faculty of Engineering - Department of Systems and Biomedical Engineering
520 ## - SUMMARY, ETC.
Summary, etc. Lung cancer is one of the most serious cancers in the world with the minimum survival rate. Lung nodules may be isolated from (solitary) or attached to (juxtapleural) other. In this paper a Computer Aided Diagnosis system is proposed to classify between solitary nodule and juxtapleural nodule inside the lungs.Two main auto-diagnostic schemes of supervised learning for classification are achieved.Three segmentation approaches are proposed.The three classifiers of the first scheme are K-Nearest Neighborhood, Artificial Neural Network and Support Vector Machine. In the second scheme, Deep Convolutional neural networksare used. Because of limited data sample and imbalanced data, 10-fold cross validation and random oversampling are used.The 3D reconstruction of pulmonary nodules based on the surface rendering technique and visualization by 3D slicer are achieved
530 ## - ADDITIONAL PHYSICAL FORM AVAILABLE NOTE
Additional physical form available note Issued also as CD
653 #4 - INDEX TERM--UNCONTROLLED
Uncontrolled term 3D Reconstruction
653 #4 - INDEX TERM--UNCONTROLLED
Uncontrolled term Deep learning
653 #4 - INDEX TERM--UNCONTROLLED
Uncontrolled term Maximum Intensity Projection
700 0# - ADDED ENTRY--PERSONAL NAME
Personal name Mai Said Mabrouk ,
Relator term
700 0# - ADDED ENTRY--PERSONAL NAME
Personal name Manal Abdelwahed ,
Relator term
905 ## - LOCAL DATA ELEMENT E, LDE (RLIN)
Cataloger Nazla
Reviser Revisor
905 ## - LOCAL DATA ELEMENT E, LDE (RLIN)
Cataloger Shimaa
Reviser Cataloger
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme Dewey Decimal Classification
Koha item type Thesis
Holdings
Source of classification or shelving scheme Not for loan Home library Current library Date acquired Full call number Barcode Date last seen Koha item type Copy number
Dewey Decimal Classification   المكتبة المركزبة الجديدة - جامعة القاهرة قاعة الرسائل الجامعية - الدور الاول 11.02.2024 Cai01.13.03.Ph.D.2021.Ay.A 01010110084851000 22.09.2023 Thesis  
Dewey Decimal Classification   المكتبة المركزبة الجديدة - جامعة القاهرة مخـــزن الرســائل الجـــامعية - البدروم 11.02.2024 Cai01.13.03.Ph.D.2021.Ay.A 01020110084851000 22.09.2023 CD - Rom 84851.CD