Content-based image retrieval for lung nodule classification using texture features and learned distance metric
Similarity measurement of lung nodules is a critical component in content-based image
retrieval (CBIR), which can be useful in differentiating between benign and malignant lung …
retrieval (CBIR), which can be useful in differentiating between benign and malignant lung …
Content-based image retrieval system for pulmonary nodules: assisting radiologists in self-learning and diagnosis of lung cancer
Visual information of similar nodules could assist the budding radiologists in self-learning.
This paper presents a content-based image retrieval (CBIR) system for pulmonary nodules …
This paper presents a content-based image retrieval (CBIR) system for pulmonary nodules …
An efficient content-based image retrieval system for the diagnosis of lung diseases
The main problem in content-based image retrieval (CBIR) systems is the semantic gap
which needs to be reduced for efficient retrieval. The common imaging signs (CISs) which …
which needs to be reduced for efficient retrieval. The common imaging signs (CISs) which …
Similarity measurement of lung masses for medical image retrieval using kernel based semisupervised distance metric
Purpose: To develop a new algorithm to measure the similarity between the query lung
mass and reference lung mass data set for content‐based medical image retrieval (CBMIR) …
mass and reference lung mass data set for content‐based medical image retrieval (CBMIR) …
Content-based image retrieval for pulmonary computed tomography nodule images
Research studies have shown that advances in computed tomography (CT) technology
allow better detection of pulmonary nodules by generating higher-resolution images …
allow better detection of pulmonary nodules by generating higher-resolution images …
Lung nodule classification by jointly using visual descriptors and deep features
Classifying benign and malignant lung nodules using the thoracic computed tomography
(CT) screening is the primary method for early diagnosis of lung cancer. Despite of their …
(CT) screening is the primary method for early diagnosis of lung cancer. Despite of their …
[PDF][PDF] Enhancing transferability of features from pretrained deep neural networks for lung nodule classification
Among most popular feature extractors, pretrained deep neural networks play a central role
in transfer learning to extract high-level feature on small datasets. The transferable …
in transfer learning to extract high-level feature on small datasets. The transferable …
Unsupervised feature selection applied to content-based retrieval of lung images
This paper describes a new hierarchical approach to content-based image retrieval called
the" customized-queries" approach (CQA). Contrary to the single feature vector approach …
the" customized-queries" approach (CQA). Contrary to the single feature vector approach …
Semantic and content-based medical image retrieval for lung cancer diagnosis with the inclusion of expert knowledge and proven pathology
P Aggarwal, R Vig, HK Sardana - 2013 IEEE Second …, 2013 - ieeexplore.ieee.org
This paper involves the analysis and experimentation of chest CT scan data for the detection
and diagnosis of lung cancer. In lung cancer computer-aided diagnosis (CAD) systems …
and diagnosis of lung cancer. In lung cancer computer-aided diagnosis (CAD) systems …
Feature representation using deep autoencoder for lung nodule image classification
K Mao, R Tang, X Wang, W Zhang, H Wu - Complexity, 2018 - Wiley Online Library
This paper focuses on the problem of lung nodule image classification, which plays a key
role in lung cancer early diagnosis. In this work, we propose a novel model for lung nodule …
role in lung cancer early diagnosis. In this work, we propose a novel model for lung nodule …