Multiclass Classification of Cervical Cancer Tissues by Hidden Markov Model

نویسندگان

  • Sabyasachi Mukhopadhyay
  • Sanket Nandan
  • Indrajit Kurmi
چکیده

In this paper, we report a hidden Markov model based multiclass classification of cervical cancer tissues. This model has been validated directly over time series generated by the medium refractive index fluctuations extracted from differential interference contrast images of healthy and different stages of cancer tissues. The method shows promising results for multiclass classification with higher accuracy. KeywordsDifferential Interference Contrast (DIC) images, Hidden Markov Model, Tissue Engineering.

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

A multi-class classification strategy for Fisher scores: Application to signer independent sign language recognition

Fisher kernels combine the powers of discriminative and generative classifiers by mapping the variable-length sequences to a new fixed length feature space, called the Fisher score space. The mapping is based on a single generative model and the classifier is intrinsically binary. We propose a strategy that applies a multiclass classification on each Fisher score space and combines the decision...

متن کامل

Using SVM and Error-correcting Codes for M Meeting Cor

Accurate classification of dialog acts (DAs) is important for many spoken language applications. Different methods have been proposed such as hidden Markov models (HMM), maximum entropy (Maxent), graphical models, and support vector machines (SVMs). In this paper, we investigate using SVMs for multiclass DA classification in the ICSI meeting corpus. We evaluate (1) representing DA tagging direc...

متن کامل

A generalization of Profile Hidden Markov Model (PHMM) using one-by-one dependency between sequences

The Profile Hidden Markov Model (PHMM) can be poor at capturing dependency between observations because of the statistical assumptions it makes. To overcome this limitation, the dependency between residues in a multiple sequence alignment (MSA) which is the representative of a PHMM can be combined with the PHMM. Based on the fact that sequences appearing in the final MSA are written based on th...

متن کامل

Evaluation of the Hidden Markov Model for Detection of P300 in EEG Signals

Introduction: Evoked potentials arisen by stimulating the brain can be utilized as a communication tool  between humans and machines. Most brain-computer interface (BCI) systems use the P300 component,  which is an evoked potential. In this paper, we evaluate the use of the hidden Markov model (HMM) for  detection of P300.  Materials and Methods: The wavelet transforms, wavelet-enhanced indepen...

متن کامل

Automated Tumor Segmentation Based on Hidden Markov Classifier using Singular Value Decomposition Feature Extraction in Brain MR images

ntroduction: Diagnosing brain tumor is not always easy for doctors, and existence of an assistant that                                                      facilitates the interpretation process is an asset in the clinic. Computer vision techniques are devised to aid the clinic in detecting tumors based on a database of tumor c...

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:
  • CoRR

دوره abs/1512.06014  شماره 

صفحات  -

تاریخ انتشار 2015