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Content based image retrieval

Yingying Xu, Lanfen Lin, Hongjie Hu, Dan Wang, Wenchao Zhu, Jian Wang, Xian-Hua Han, Yen-Wei Chen
PURPOSE: The bag of visual words (BoVW) model is a powerful tool for feature representation that can integrate various handcrafted features like intensity, texture, and spatial information. In this paper, we propose a novel BoVW-based method that incorporates texture and spatial information for the content-based image retrieval to assist radiologists in clinical diagnosis. METHODS: This paper presents a texture-specific BoVW method to represent focal liver lesions (FLLs)...
November 5, 2017: International Journal of Computer Assisted Radiology and Surgery
Dirk Tiede, Andrea Baraldi, Martin Sudmanns, Mariana Belgiu, Stefan Lang
Spatiotemporal analytics of multi-source Earth observation (EO) big data is a pre-condition for semantic content-based image retrieval (SCBIR). As a proof of concept, an innovative EO semantic querying (EO-SQ) subsystem was designed and prototypically implemented in series with an EO image understanding (EO-IU) subsystem. The EO-IU subsystem is automatically generating ESA Level 2 products (scene classification map, up to basic land cover units) from optical satellite data. The EO-SQ subsystem comprises a graphical user interface (GUI) and an array database embedded in a client server model...
2017: Eur J Remote Sens
Guohui Wei, He Ma, Wei Qian, Hongyang Jiang, Xinzhuo Zhao
Similarity metric of the lung nodules can be useful in differentiating between benign and malignant lung nodule lesions on computed tomography (CT). Unlike previous computerized schemes, which focus on the features extracting, we concentrate on similarity metric of the lung nodules. In this study, we first assemble a lung nodule dataset which is from LIDC-IDRI lung CT images. This dataset includes 746 lung nodules in which 375 domain radiologists identified malignant nodules and 371 domain radiologists-identified benign nodules...
July 2017: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Jing Zhang, Wenhao Geng, Xi Liang, Jiafeng Li, Li Zhuo, Qianlan Zhou
Although many content-based image retrieval systems have been developed, few studies have focused on hyperspectral remote sensing images. In this paper, a hyperspectral remote sensing image retrieval system based on spectral and texture features is proposed. The main contributions are fourfold: (1) considering the "mixed pixel" in the hyperspectral image, endmembers as spectral features are extracted by an improved automatic pixel purity index algorithm, then the texture features are extracted with the gray level co-occurrence matrix; (2) similarity measurement is designed for the hyperspectral remote sensing image retrieval system, in which the similarity of spectral features is measured with the spectral information divergence and spectral angle match mixed measurement and in which the similarity of textural features is measured with Euclidean distance; (3) considering the limited ability of the human visual system, the retrieval results are returned after synthesizing true color images based on the hyperspectral image characteristics; (4) the retrieval results are optimized by adjusting the feature weights of similarity measurements according to the user's relevance feedback...
June 1, 2017: Applied Optics
Mengqiu Hu, Yang Yang, Fumin Shen, Ning Xie, Heng Tao Shen
Large-scale search methods are increasingly critical for many content-based visual analysis applications, among which hashing-based approximate nearest neighbor search techniques have attracted broad interests due to their high efficiency in storage and retrieval. However, existing hashing works are commonly designed for measuring data similarity by the Euclidean distances. In this paper, we focus on the problem of learning compact binary codes using the cosine similarity. Specifically, we proposed novel angular reconstructive embeddings (ARE) method, which aims at learning binary codes by minimizing the reconstruction error between the cosine similarities computed by original features and the resulting binary embeddings...
February 2018: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
Peizhong Liu, Jing-Ming Guo, Chi-Yi Wu, Danlin Cai
This paper presents an effective image retrieval method by combining high-level features from Convolutional Neural Network (CNN) model and low-level features from Dot-Diffused Block Truncation Coding (DDBTC). The low-level features, e.g., texture and color, are constructed by VQ-indexed histogram from DDBTC bitmap, maximum, and minimum quantizers. Conversely, high-level features from CNN can effectively capture human perception. With the fusion of the DDBTC and CNN features, the extended deep learning two-layer codebook features (DL-TLCF) is generated using the proposed two-layer codebook, dimension reduction, and similarity reweighting to improve the overall retrieval rate...
August 29, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
Jamil Ahmad, Khan Muhammad, Sung Wook Baik
In recent years, image databases are growing at exponential rates, making their management, indexing, and retrieval, very challenging. Typical image retrieval systems rely on sample images as queries. However, in the absence of sample query images, hand-drawn sketches are also used. The recent adoption of touch screen input devices makes it very convenient to quickly draw shaded sketches of objects to be used for querying image databases. This paper presents a mechanism to provide access to visual information based on users' hand-drawn partially colored sketches using touch screen devices...
2017: PloS One
Hyunmin Kim, Do-Young Kim, Kyung-Il Joo, Jung-Hye Kim, Soon Moon Jeong, Eun Seong Lee, Jeong-Hoon Hahm, Kyuhyung Kim, Dae Woon Moon
In this study, we used spectrally focused coherent anti-Stokes Raman scattering (spCARS) microscopy assisted by sum-frequency generation (SFG) to monitor the variations in the structural morphology and molecular vibrations of a live muscle of Caenorhabditis elegans. The subunits of the muscle sarcomeres, such as the M-line, myosin, dense body, and α-actinin, were alternatively observed using spCARS microscopy for different sample orientations, with the guidance of a myosin positional marker captured by SFG microscopy...
August 23, 2017: Scientific Reports
Chi-Hsun Chang, Dan Nemrodov, Andy C H Lee, Adrian Nestor
Visual memory for faces has been extensively researched, especially regarding the main factors that influence face memorability. However, what we remember exactly about a face, namely, the pictorial content of visual memory, remains largely unclear. The current work aims to elucidate this issue by reconstructing face images from both perceptual and memory-based behavioural data. Specifically, our work builds upon and further validates the hypothesis that visual memory and perception share a common representational basis underlying facial identity recognition...
July 26, 2017: Scientific Reports
Yushan Zheng, Zhiguo Jiang, Haopeng Zhang, Fengying Xie, Yibing Ma, Huaqiang Shi, Yu Zhao
Content-based image retrieval (CBIR) has been widely researched for histopathological images. It is challenging to retrieve contently similar regions from histopathological whole slide images (WSIs) for regions of interest (ROIs) in different size. In this paper, we propose a novel CBIR framework for database that consists of WSIs and size-scalable query ROIs. Each WSI in the database is encoded into a matrix of binary codes. When retrieving, a group of region proposals that have similar size with the query ROI are firstly located in the database through an efficient table-lookup approach...
July 4, 2017: IEEE Journal of Biomedical and Health Informatics
Arnau Ramisa, Fei Yan, Francesc Moreno-Noguer, Krystian Mikolajczyk
Current approaches lying in the intersection of computer vision and NLP have achieved unprecedented breakthroughs in tasks like automatic captioning or image retrieval. Most of these methods, though, rely on training sets of images associated with annotations that specifically describe the visual content. This paper proposes going a step further and explores more complex cases where textual descriptions are loosely related to images. We focus on the particular domain of News. We introduce new deep learning methods that address source and popularity prediction, article illustration, and article geolocation...
June 30, 2017: IEEE Transactions on Pattern Analysis and Machine Intelligence
Nicola L Stevenson, Ian J White, Jessica J McCormack, Christopher Robinson, Daniel F Cutler, Thomas D Nightingale
Weibel-Palade bodies (WPBs), the storage organelles of endothelial cells, are essential to normal haemostatic and inflammatory responses. Their major constituent protein is von Willebrand factor (VWF) which, following stimulation with secretagogues, is released into the blood vessel lumen as large platelet-catching strings. This exocytosis changes the protein composition of the cell surface and also results in a net increase in the amount of plasma membrane. Compensatory endocytosis is thought to limit changes in cell size and retrieve fusion machinery and other misplaced integral membrane proteins following exocytosis; however, little is known about the extent, timing, mechanism and precise function of compensatory endocytosis in endothelial cells...
August 1, 2017: Journal of Cell Science
Xiaoming Zhang, Senzhang Wang, Zhoujun Li, Shuai Ma
Landmark retrieval is to return a set of images with their landmarks similar to those of the query images. Existing studies on landmark retrieval focus on exploiting the geometries of landmarks for visual similarity matches. However, the visual content of social images is of large diversity in many landmarks, and also some images share common patterns over different landmarks. On the other side, it has been observed that social images usually contain multimodal contents, i.e., visual content and text tags, and each landmark has the unique characteristic of both visual content and text content...
June 20, 2017: IEEE Transactions on Cybernetics
Qinnan Zhang, Liyun Zhong, Ping Tang, Yingjie Yuan, Shengde Liu, Jindong Tian, Xiaoxu Lu
Cell refractive index, an intrinsic optical parameter, is closely correlated with the intracellular mass and concentration. By combining optical phase-shifting interferometry (PSI) and atomic force microscope (AFM) imaging, we constructed a label free, non-invasive and quantitative refractive index of single cell measurement system, in which the accurate phase map of single cell was retrieved with PSI technique and the cell morphology with nanoscale resolution was achieved with AFM imaging. Based on the proposed AFM/PSI system, we achieved quantitative refractive index distributions of single red blood cell and Jurkat cell, respectively...
May 31, 2017: Scientific Reports
Li Tian, Patrick Lee, Burapol Singhana, Aaron Chen, Yang Qiao, Linfeng Lu, Jonathan O Martinez, Ennio Tasciotti, Adam Melancon, Steven Huang, Mitch Eggers, Marites P Melancon
Failure to remove a retrievable inferior vena cava (IVC) filter can cause severe complications with high treatment costs. Polydioxanone (PPDO) has been shown to be a good candidate material for resorbable IVC filters. However, PPDO is radioluscent under conventional imaging modalities. Thus, the positioning and integrity of these PPDO filters cannot be monitored by computed tomography (CT) or x-ray. Here we report the development of radiopaque PPDO IVC filters based on gold nanoparticles (AuNPs). Commercially available PPDO sutures were infused with AuNPs...
May 19, 2017: Scientific Reports
Manish Sapkota, Fujun Liu, Yuanpu Xie, Hai Su, Fuyong Xing, Lin Yang
Idiopathic Inflammatory Myopathy (IIM) is a common skeletal muscle disease that relates to weakness and inflammation of muscle. Early diagnosis and prognosis of different types of IIMs will guide the effective treatment. Interpretation of digitized images of the cross section muscle biopsy, which is currently done manually, provides the most reliable diagnostic information. With the increasing volume of images, the management and manual interpretation of the digitized muscle images suffer from low efficiency and high interobserver variabilities...
April 13, 2017: IEEE Journal of Biomedical and Health Informatics
Jian Wang, Xian-Hua Han, Yingying Xu, Lanfen Lin, Hongjie Hu, Chongwu Jin, Yen-Wei Chen
Characterization and individual trait analysis of the focal liver lesions (FLL) is a challenging task in medical image processing and clinical site. The character analysis of a unconfirmed FLL case would be expected to benefit greatly from the accumulated FLL cases with experts' analysis, which can be achieved by content-based medical image retrieval (CBMIR). CBMIR mainly includes discriminated feature extraction and similarity calculation procedures. Bag-of-Visual-Words (BoVW) (codebook-based model) has been proven to be effective for different classification and retrieval tasks...
2017: International Journal of Biomedical Imaging
Miguel Fdo Salazar, Martha Lilia Tena-Suck, Alma Ortiz-Plata, Citlaltepetl Salinas-Lara, Daniel Rembao-Bojórquez
"Lipomatous" and "extensively vacuolated" are descriptive captions that have been used to portray a curious subset of ependymomas distinctively bearing cells with a large vacuole pushing the nucleus to the periphery and, thus, simulating a signet-ring cell appearance. Here, we would like to report the first ependymoma of this kind in a Latin American institution. A 16-year-old boy experienced cephalea during three months. Magnetic resonance imaging scans showed a left paraventricular tumour which corresponded to anaplastic ependymoma...
2017: Case Reports in Pathology
Wengang Zhou, Houqiang Li, Jian Sun, Qi Tian
In content-based image retrieval, SIFT feature and the feature from deep convolutional neural network (CNN) have demonstrated promising performance. To fully explore both visual features in a unified framework for effective and efficient retrieval, we propose a collaborative index embedding method to implicitly integrate the index matrices of them. We formulate the index embedding as an optimization problem from the perspective of neighborhood sharing and solve it with an alternating index update scheme. After the iterative embedding, only the embedded CNN index is kept for on-line query, which demonstrates significant gain in retrieval accuracy, with very economical memory cost...
March 1, 2017: IEEE Transactions on Pattern Analysis and Machine Intelligence
Alexandra La Cruz, Ruben Medina, Francisco Vega, Wilson Perez, Blanca Ochoa, Victor Saquicela, Mauricio Espinoza, Lizandro Solano-Quinde, Maria-Esther Vidal
Teleradiology systems tackle the problem of transferring radiological images between medical image workstations for facilitating different medical activities, e.g., diagnosis, treatment and follow up a patient, medical training, or consulting second opinion. Nowadays, m-Health (aka mobile health) is becoming popular because of high quality of mobile displays, although remains a work in progress. In this paper a mobile teleradiology system is reported, which main contribution is the development of a platform: (1) supported by a Grid infrastructure, (2) using biomedical ontologies for adding semantic annotations on medical images, and (3) supporting semantic and content-based image retrieval...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
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