Biomedical Projects

 Content-Based Brain Tumor Retrieval for MR Images Using Transfer Learning

This paper presents an automatic content-based image retrieval (CBIR) system for brain tumors on T1- weighted contrast-enhanced magnetic resonance images (CE-MRI). The key challenge in CBIR systems for MR images is the semantic gap between the low-level visual information captured by the MRI machine and the high-level information perceived by the human evaluator. The traditional feature extraction methods focus only on low-level or high-level features and use some handcrafted features to reduce this gap. It is necessary to design a feature extraction framework to reduce this gap without using handcrafted features by encoding/combining low-level and high-level features. Deep learning is very powerful for feature representation that can depict low-level and high-level information completely and embed the phase of feature extraction in self-learning. Therefore, we propose a deep convolutional neural network VGG19-based novel feature extraction framework and apply closed- form metric learning to measure the similarity between the query image and database images. Furthermore, we adopt transfer learning and propose a block-wise fine-tuning strategy to enhance the retrieval performance. The extensive experiments are performed on a publicly available CE-MRI dataset that consists of three types of brain tumors (i.e., glioma, meningioma, and pituitary tumor) collected from 233 patients with a total of 3064 images across the axial, coronal, and sagittal views.

2WGAN-Based Synthetic Minority Over-Sampling Technique: Improving Semantic Fine- Grained Classification for Lung Nodules in CT Images

3Deep Belief Network Modeling for Automatic Liver Segmentation

4Classification of Breast Cancer Histology Images Using Multi-Size and Discriminative Patches Based on Deep Learning

5Convolutional Neural Network (CNN) Based Three Dimensional Tumor Localization Using Single X-Ray Projection

6Intrinsic Image Decomposition-Based Grey and Pseudo-Color Medical Image Fusion

7Multi-Resolution CNN and Knowledge Transfer for Candidate Classification in Lung Nodule Detection

8Brain MRI Image Classification for Cancer Detection Using Deep Wavelet Auto encoder- Based Deep Neural Network

9Lung Nodule Detection with Deep Learning in 3D Thoracic MR Images

10Skin Lesion Classification Using Convolutional Neural Network with Novel Regularizer

11A New Hybrid Algorithm for Retinal Vessels Segmentation on Fundus Images

12Multi-Modal Medical Image Fusion with Adaptive Weighted Combination of NSST Bands Using Chaotic Grey Wolf Optimization

13Diagnosis and Data Probability Decision Based on Non-Small Cell Lung Cancer in Medical System

14Robust Retinal Image Enhancement via Dual-Tree Complex Wavelet Transform and Morphology-Based Method

15Medical Image Retrieval Based on Convolutional Neural Network and Supervised Hashing

16An Improved Confidence Connected Liver Segmentation Method Based on Three Views of CT Images

17Analyzing the Dynamics of Lung Cancer Imaging Data Using Refined Fuzzy Entropy Methods by Extracting Different Features

18Studies on Different CNN Algorithms for Face Skin Disease Classification Based on Clinical Images

19Multi-Classification of Brain Tumor Images Using Deep Neural Network

20Fine-Grained Classification of Cervical Cells Using Morphological and Appearance Based Convolutional Neural Networks

21A Hierarchical Image Matting Model for Blood Vessel Segmentation in Fundus Images

22Robust retinal blood vessel segmentation using hybrid active contour model

23Multi-objective based radiomic feature selection for lesion malignancy classification

24Discriminative Feature Learning with Foreground Attention for Person Re-identification

25Blood Cell Classification Based on Hyper spectral Imaging with Modulated Gabor and CNN