Show/Hide Menu
Hide/Show Apps
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Open Science Policy
Open Science Policy
Open Access Guideline
Open Access Guideline
Postgraduate Thesis Guideline
Postgraduate Thesis Guideline
Communities & Collections
Communities & Collections
Help
Help
Frequently Asked Questions
Frequently Asked Questions
Guides
Guides
Thesis submission
Thesis submission
MS without thesis term project submission
MS without thesis term project submission
Publication submission with DOI
Publication submission with DOI
Publication submission
Publication submission
Supporting Information
Supporting Information
General Information
General Information
Copyright, Embargo and License
Copyright, Embargo and License
Contact us
Contact us
Kanserli dokuların mikroskop görüntülerinde kanser kök hücre oranın otomatik olarak belirlenmesi ve klinikte kullanılacak yazılım geliştirilmesi
Download
TVRVM01EVTE.pdf
Date
2016
Author
Demir, Gündüz Çiğdem
Güzelcan, Akhan Ece
Arslan, Tunç Musa
Yorulmaz, Onur
Fayetörbay, Rümeysa
Erşahin, Tülin
Mohammadvand, Navid
Örsçelik, Gökçe Simge
Üner, Ayşegül
Çetin, Enis Ahmet
Oğuz, Oğuzhan
Doğan, Deniz
Koyuncu, Fahrettin Can
Badawı, Diaa
Atalay, Rengül
Metadata
Show full item record
This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
.
Item Usage Stats
336
views
787
downloads
Cite This
Kanser anormal hücrelerin kontrolsüz çoğalması ve yayılması olarak tanımlanan karmaşık bir hastalıktır. Bu nedenle kanser dokusu farklı özellikleri olan-ek popülasyon denilen-hücre gruplarını içerir. Bu hücrelerden olan kanser kök hücreleri normal kök hücreleri gibi kendini yenileme ve farklılaşma özelliklerini taşırken normal kök hücrelerinin aksine homeostatik kontrolleri olmayan, yani farklılaşma özelliklerini dengeleyip, çevresel sinyallere göre programlama özellikleri olmayan hücrelerdir. Bu özellikleri dolayısıyla da son yıllarda kanser kök hücre popülasyonu kanserin kötü prognozundan sorumlu hücreler olarak tanımlanmaktadırlar. Bu bağlamda kanser tedavisinde kanser kök hücre oran bilgisi, hastaya verilecek tedavinin planlanması amacıyla kullanılabilir. Hekimler kanserli dokunun kanser kök hücre popülasyon onarına göre henüz kanser metastaz yapmamış bile olsa bireye özgü tedavi yaklaşımı izlenebilir. Gerçekleştirilen bu proje kapsamında, kanserli parafin bloklara gömülü doku biyopsi örneklerinde, kanser kök hücre tanımlama öngörü aracını geliştirdik. Kovaryans matrisine dayalı sınıflandırıcılara ve Ana Bileşenler Analizi (PCA) algoritması sonucunda üç sınıf H&E boyanmış karaciğer kanseri dokularının sınıflandırma probleminde 76.0% imge sınıflandırma başarısı elde edilmiştir. Ana Bileşenler Analizi kanser hücresi belirleme probleminde %90’nın üstünde başarı ve kovaryans matrisine dayalı sınıflandırıcılar ile üç sınıf ayrıştırma probleminde %90’a yakın başarı sağlanmıştır. Kanserli hastalarda bireye ve hedefe yönelik tedavi yol haritasının belirlenmesine destek olabilecek ve hastalığın tedavisinde ve prognozunda iyileştirme sağlayabilecek yazılımı hekimlerin kullanıma sunduk. CANSTEM yazılıma http://users.metu.edu.tr/rengul/canstem.html adresinden ulaşılabilir.
Subject Keywords
Kanser kök hücre
,
Makine ile öğrenme
,
İmmunohistokimya
,
Tedavi
,
Prognoz
URI
https://app.trdizin.gov.tr/publication/project/detail/TVRVM01EVTE
https://hdl.handle.net/11511/49402
Collections
Graduate School of Informatics, Project and Design
Suggestions
OpenMETU
Core
Effects of novel compound derived from vitamin e on prostate cancer cell line
Ergen, Nuri; Severcan, Feride; Department of Biology (2016)
Cancer is a complex disease characterized by uncontrolled cell proliferation, invasion and metastasis. It is known that vitamins having high antioxidant capacity, like vitamin A, C and E, play important roles in adjuvant therapy and as cancer protective agents. Vitamin E is a group of fat soluble antioxidant nutrients consisting of tocopherols and tocotrienols. Various research has been performed on the utility of vitamin E derivatives on cancer treatment. Energy metabolism of cells alters during cancer pro...
Analysis of 3'UTR shortening events in breast cancer
Baloğlu, Onur; Can, Tolga; Department of Bioinformatics (2013)
Cancer is the collective term used to describe a diverse group of diseases that share certain hallmarks, which in turn enables the affected cells to sustain an uncontrolled cell growth. Despite the increasing efforts and advances in cancer therapies, cancers are still responsible for approximately 10% of all the deaths worldwide. Furthermore, the increase in the average human lifespan will further contribute to the cancer incidences. This brings the necessity to focus our efforts on early detection and effe...
Analyses and modeling of ovarian cancer microarray data
Karakelle, Barış S; Purutçuoğlu Gazi, Vilda; Department of Biomedical Engineering (2019)
Ovarian cancer is one of the common cancer types among other oncological diseases. The major causes of this cancer can be listed as age, obesity, hormone therapy, material inheritance and contraceptive pills. Due to its generality and importance, many researches have been conducted from distinct labs about this illness and its plausible causes have been intensively investigated either inmicroarray studies, where just part of the related genes are detected, or in thepairwise correlation analyses between the ...
Cell-surface interactions in a breast cancer model
Antmen, Ezgi; Hasırcı, Vasıf Nejat; Demirci, Utkan; Department of Biotechnology (2017)
Breast cancer, is one of the most commonly diagnosed cancers, has a high mortality rate. One in every eight women (12.3%) develops breast cancer at some stage of their lives and this is the cause of about 15% of cancer deaths in women and 3% of total deaths. It is therefore important to study the behavior of breast cancer cells. Measurement of the mechanical properties of cancer cells leads to new insights such as that cancer cells are softer than healthy cells. Also, metastatic cancer cells were found to b...
Model comparison for gynecological cancer datasets and selection of threshold value
Bahçivancı, Başak; Purutçuoğlu Gazi, Vilda; Department of Statistics (2019)
Cancer is a very common system’s disease with its structural and functional complexities caused by high dimension and serious correlation of genes as well as sparsity of gene interactions. Hereby, different mathematical models have been suggested in the literature to unravel these challenges. Among many alternates, in this study we use the Gaussian graphical model, Gaussian copula graphical model and loop-based multivariate adaptive regression splines with/without interaction models due to their advantages ...
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
G. Ç. Demir et al., “Kanserli dokuların mikroskop görüntülerinde kanser kök hücre oranın otomatik olarak belirlenmesi ve klinikte kullanılacak yazılım geliştirilmesi,” 2016. Accessed: 00, 2020. [Online]. Available: https://app.trdizin.gov.tr/publication/project/detail/TVRVM01EVTE.