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 |