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Lung Classification Using Image Processing

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Abstract:

Effective identification of lung cancer at an initial stage is an important and crucial aspect of image processing. Several Segmentation  methods have been used to detect lung cancer at early stage. In this paper, an approach has been presented which will diagnose lung cancer at an initial stage using CT scan images. One of the key challenges is to remove white Gaussian noise from the CT scan image, which is done using Gabor filter and to segment the lung is transform method dual tree complex wavelet transform (DTCWT) is used. The GLCM features are extracted from the processed image to form feature vector. These features can be compared with database images using classifier as neural networks . After identifying the effected disease as normal or tumourous we are segmenting the tumourous image by using watershed segmentation to get colour features of tumour after getting color features for shape features we are applying FCM. In this paper CNN are applied for the detection of lung cancer to find the severity of disease (stage I or stage II) and we find different quality attributes such as accuracy, sensitivity(recall), precision and specificity to know the performance.

 

 Existing System:

  • Watershed
  • Thresholding

 

Drawbacks:

  • Database is not used
  • If thresholding is low accurate detection not possible

 

Proposed Method:

  • DTCWT
  • CNN
  • Watershed+ FCM

 

Advantages:

  • Noise is reduced using gabor filter
  • DTCWT is done for eliminating high frequencies
  • CNN as a classifier it checks more inputs to classify
  • By using FCM we get shape features of tumour

 

 

Block diagram:

Lung Classification Using Image Processing

 

Methodology:

  • CT Images
  • GLCM
  • FCM
  • DTCTWT

 

Applications:

  • Bio medical
  • Cancer detection and diagnoisis

 

Software  Used:

  • Matlab 7.5 above

 

 References:

[1] Anita chaudhary, SonitSukhraj Singh “Lung Cancer Detection on CT Images by Using Image Processing”2012 International Conference on Computing Sciences

[2] NihadMesanovic, HarisHuseinagic, Matija Males, , MislavGrgic, Emir Skejic, MuamerSmajlovic ”Automatic CT Image Segmentation of the Lungs with Region Growing Algorithm”

[3] SayaniNandy, Nikita Pandey A Novel Approach of Cancerous Cells Detection from Lungs CT Scan Images’’ International Journal of Advanced Research in Computer Science and Software Engineering Volume 2, Issue 8, August 2012

[4] Prof. Samir Kumar Bandyopadhyay “Edge Detection From Ct Images Of Lung’’ International Journal Of Engineering Science & Advanced Technology Volume – 2, Issue – 1, 34 – 37

[5] FatmTaher, NaoufelWerghi and Hussain Al-Ahmad “Extraction of Sputum Cells using Thresholding Techniques for Lung Cancer Detection” 2012 International Conference on Innovations in Information Technology

[6] QinghuaJi,Ronggang Shi “A Noval Method of Image Segmentation Using Watershed Transformation”2011 International Conference on Computer Science and Network Technology

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  • Price
    Free
  • Instructor pantech team
  • Duration 15 Hrs
  • Enrolled 0 student
  • Access 3 Months

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