Automatic Liver Tumor Segmentation based on Multi-level Deep Convolutional Networks and Fractal Residual Network

ABSTRACT

The liver is a very important and complex organ in our body. Efficient liver segmentation is a very important interesting and challenging task in the field of medical image processing. The abdomen consists of many organs among which the liver consists of very important parts, such as right lobule, left lobule and hepatic duct. In this research work, for computed tomography (CT) images we designed a feasible upstream approach to segment a liver region from abdomen using multi-level deep convolutional network and Fractal Residual Network (FRN). Our convolutional neural network is designed in such a way that it learns to allot different probabilities for each super pixel based on different regions of the liver by these indirectly different classes are created based on different intensities of super pixels. Further FRN is used to identify the tumor region and finally refinement of tumor segmentation is done with active contour model method. The proposed model (MDCN + FRN) is evaluated on CT images 125 patients from TCI dataset and achieved a dice similarity in an average of 0.89 in training and dice similarity in an average of 0.86 in testing. Compared to other segmentation methods, the experiment conducted shows better performance from proposed method.

KEYWORDS:

• Active contour method (ACM)
• Convolutional neural network (CNN)
• Fractal residual network (FRN)
• Liver tumor segmentation
• Multilevel deep convolutional network (MDCN)

Additional information

Notes on contributors

B.C. Anil

BC Anil working as assistant professor in the Department of Information Science and Engineering, at JSS Academy of Technical Education, Bengaluru, Karnataka, India from 2013. His area of research works are data mining and image processing. Email: [email protected]

P. Dayananda

P Dayananda is currently working as professor & HOD in the Department of ISE at JSSATE. He Obtained PhD degree from VTU and MTech degree from RVCE. His focus area is image processing & information retrieval. He was with MSRIT, Bengaluru, India. He has published many papers in national and international journals in the field of image processing and retrieval.