Automated Cell Selection Using Support Vector Machine for Application to Spectral Nanocytology
المؤلفون المشاركون
Miao, Qin
Derbas, Justin
Eid, Aya
Subramanian, Hariharan
Backman, Vadim
المصدر
العدد
المجلد 2016، العدد 2016 (31 ديسمبر/كانون الأول 2016)، ص ص. 1-10، 10ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2016-01-19
دولة النشر
مصر
عدد الصفحات
10
التخصصات الرئيسية
الملخص EN
Partial wave spectroscopy (PWS) enables quantification of the statistical properties of cell structures at the nanoscale, which has been used to identify patients harboring premalignant tumors by interrogating easily accessible sites distant from location of the lesion.
Due to its high sensitivity, cells that are well preserved need to be selected from the smear images for further analysis.
To date, such cell selection has been done manually.
This is time-consuming, is labor-intensive, is vulnerable to bias, and has considerable inter- and intraoperator variability.
In this study, we developed a classification scheme to identify and remove the corrupted cells or debris that are of no diagnostic value from raw smear images.
The slide of smear sample is digitized by acquiring and stitching low-magnification transmission.
Objects are then extracted from these images through segmentation algorithms.
A training-set is created by manually classifying objects as suitable or unsuitable.
A feature-set is created by quantifying a large number of features for each object.
The training-set and feature-set are used to train a selection algorithm using Support Vector Machine (SVM) classifiers.
We show that the selection algorithm achieves an error rate of 93% with a sensitivity of 95%.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Miao, Qin& Derbas, Justin& Eid, Aya& Subramanian, Hariharan& Backman, Vadim. 2016. Automated Cell Selection Using Support Vector Machine for Application to Spectral Nanocytology. BioMed Research International،Vol. 2016, no. 2016, pp.1-10.
https://search.emarefa.net/detail/BIM-1098390
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Miao, Qin…[et al.]. Automated Cell Selection Using Support Vector Machine for Application to Spectral Nanocytology. BioMed Research International No. 2016 (2016), pp.1-10.
https://search.emarefa.net/detail/BIM-1098390
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Miao, Qin& Derbas, Justin& Eid, Aya& Subramanian, Hariharan& Backman, Vadim. Automated Cell Selection Using Support Vector Machine for Application to Spectral Nanocytology. BioMed Research International. 2016. Vol. 2016, no. 2016, pp.1-10.
https://search.emarefa.net/detail/BIM-1098390
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1098390
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر