MARC details
| 000 -LEADER |
|---|
| fixed length control field |
02052cam a2200313 a 4500 |
| 003 - CONTROL NUMBER IDENTIFIER |
|---|
| control field |
EG-GiCUC |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
|---|
| fixed length control field |
210228s2020 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 |
M.Sc |
| 099 ## - LOCAL FREE-TEXT CALL NUMBER (OCLC) |
|---|
| Classification number |
Cai01.13.03.M.Sc.2020.Ah.B |
| 100 0# - MAIN ENTRY--PERSONAL NAME |
|---|
| Personal name |
Ahmed Mostafa Salem Hijab |
| 245 10 - TITLE STATEMENT |
|---|
| Title |
Breast cancer classification in ultras und oimages using transfer learning / |
| Statement of responsibility, etc. |
Ahmed Mostafa Salem Hijab ; Supervised Ayman M. Eldeib , Muhammad A. Rushdi |
| 246 15 - VARYING FORM OF TITLE |
|---|
| Title proper/short title |
تصنيف سرطان الثدى فى صور الموجات فوق الصوتية باستخدام تعلم النقل |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. |
|---|
| Place of publication, distribution, etc. |
Cairo : |
| Name of publisher, distributor, etc. |
Ahmed Mostafa Salem Hijab , |
| Date of publication, distribution, etc. |
2020 |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
54 P. : |
| Other physical details |
charts , facimiles ; |
| Dimensions |
30cm |
| 502 ## - DISSERTATION NOTE |
|---|
| Dissertation note |
Thesis (M.Sc.) - Cairo University - Faculty of Engineering - Department of Systems and Biomedical Engineering |
| 520 ## - SUMMARY, ETC. |
|---|
| Summary, etc. |
We explored three versions of a deep learning solution to computer-aided detection of ultrasound images of cancerous tumor tissues. Experimentally, our work proved that the pre-trained VGG16 model has the best outputs in the fine-tuned version. In short, our test accuracy ranges from 79% to 97%. We employed data augmentation to enlarge the amount of training data, and avoid overfitting. We have also employed the VGG16 pre-trained model, and added practical fine tuning to improve precision.This work offers a path into developing realistic and versatile deep learning frameworks for detecting breast cancer.The findings suggest that the fine-tuned model with pre-training medical data has increased the classification accuracy.These frameworks should complement and provide assistance for approaches of clinical diagnosis and treatment |
| 530 ## - ADDITIONAL PHYSICAL FORM AVAILABLE NOTE |
|---|
| Additional physical form available note |
Issued also as CD |
| 653 #4 - INDEX TERM--UNCONTROLLED |
|---|
| Uncontrolled term |
Breast lesion |
| 653 #4 - INDEX TERM--UNCONTROLLED |
|---|
| Uncontrolled term |
Convolutional neural networks |
| 653 #4 - INDEX TERM--UNCONTROLLED |
|---|
| Uncontrolled term |
Ultrasound |
| 700 0# - ADDED ENTRY--PERSONAL NAME |
|---|
| Personal name |
Ayman M. Eldeib , |
| Relator term |
|
| 700 0# - ADDED ENTRY--PERSONAL NAME |
|---|
| Personal name |
Muhammad A. Rushdi , |
| 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 |
