Texture-based segmentation and a new cell shape index for quantitative analysis of cell spreading in AFM images.

نویسندگان

  • Volkan Müjdat Tiryaki
  • Usienemnfon Adia-Nimuwa
  • Virginia M Ayres
  • Ijaz Ahmed
  • David I Shreiber
چکیده

A new cell shape index is defined for use with atomic force microscopy height images of cell cultures. The new cell shape index reveals quantitative cell spreading information not included in a conventional cell shape index. A supervised learning-based cell segmentation algorithm was implemented by texture feature extraction and a multi-layer neural network classifier. The texture feature sets for four different culture surfaces were determined from the gray level co-occurrence matrix and local statistics texture models using two feature selection algorithms and by considering computational cost. The quantitative morphometry of quiescent-like and reactive-like cerebral cortical astrocytes cultured on four different culture environments was investigated using the new and conventional cell shape index. Inclusion of cell spreading with stellation information through use of the new cell shape index was shown to change biomedical conclusions derived from conventional cell shape analysis based on stellation alone. The new CSI results showed that the quantitative astrocyte spreading and stellation behavior was induced by both the underlying substrate and the immunoreactivity of the astrocytes.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Intelligent Diagnosis of Actinic Keratosis and Squamous Cell Carcinoma of the Skin, Using Linear and Nonlinear Features Based on Image Processing Techniques

Introduction: Most skin cancers are treatable in the early stages; thus, an early and rapid diagnosis can be very important to save patients’ lives. Today, with artificial intelligence, early detection of cancer in the initial stages is possible. Method: In this descriptive-analytical study, a computerized diagnostic system based on image processing techniques was presented, which is much more ...

متن کامل

Intelligent Diagnosis of Actinic Keratosis and Squamous Cell Carcinoma of the Skin, Using Linear and Nonlinear Features Based on Image Processing Techniques

Introduction: Most skin cancers are treatable in the early stages; thus, an early and rapid diagnosis can be very important to save patients’ lives. Today, with artificial intelligence, early detection of cancer in the initial stages is possible. Method: In this descriptive-analytical study, a computerized diagnostic system based on image processing techniques was presented, which is much more ...

متن کامل

Unsupervised Texture Image Segmentation Using MRFEM Framework

Texture image analysis is one of the most important working realms of image processing in medical sciences and industry. Up to present, different approaches have been proposed for segmentation of texture images. In this paper, we offered unsupervised texture image segmentation based on Markov Random Field (MRF) model. First, we used Gabor filter with different parameters’ (frequency, orientatio...

متن کامل

A multi-scale convolutional neural network for automatic cloud and cloud shadow detection from Gaofen-1 images

The reconstruction of the information contaminated by cloud and cloud shadow is an important step in pre-processing of high-resolution satellite images. The cloud and cloud shadow automatic segmentation could be the first step in the process of reconstructing the information contaminated by cloud and cloud shadow. This stage is a remarkable challenge due to the relatively inefficient performanc...

متن کامل

Quantitative Comparison of SPM, FSL, and Brainsuite for Brain MR Image Segmentation

Background: Accurate brain tissue segmentation from magnetic resonance (MR) images is an important step in analysis of cerebral images. There are software packages which are used for brain segmentation. These packages usually contain a set of skull stripping, intensity non-uniformity (bias) correction and segmentation routines. Thus, assessment of the quality of the segmented gray matter (GM), ...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:
  • Cytometry. Part A : the journal of the International Society for Analytical Cytology

دوره 87 12  شماره 

صفحات  -

تاریخ انتشار 2015