Content-based image retrieval for digital mammography
نویسندگان
چکیده
Recent years have witnessed burgeoning interest in developing methods for automated image retrieval. This is driven largely by the rapid increase in the size of image collections in various disciplines ranging from industrial, medical, to military applications, and by the steady development of the Internet. There is an increasing demand to retrieve stored pictorial information from these database systems in an efficient manner. Traditionally, these images are retrieved based on some textual annotation. However, in many disciplines, such annotation is neither adequate for capturing the information embedded in the images nor does it provide interactive image understanding for the user because of the following reasons (Niblack, et al., 1993; Smeulders & Worring, 2000; Tagare, Jaffe, & Duncan, 1997): ABsTRAcT
منابع مشابه
A Modified Grasshopper Optimization Algorithm Combined with CNN for Content Based Image Retrieval
Nowadays, with huge progress in digital imaging, new image processing methods are needed to manage digital images stored on disks. Image retrieval has been one of the most challengeable fields in digital image processing which means searching in a big database in order to represent similar images to the query image. Although many efficient researches have been performed for this topic so far, t...
متن کاملImage retrieval using the combination of text-based and content-based algorithms
Image retrieval is an important research field which has received great attention in the last decades. In this paper, we present an approach for the image retrieval based on the combination of text-based and content-based features. For text-based features, keywords and for content-based features, color and texture features have been used. Query in this system contains some keywords and an input...
متن کاملCalcification Descriptor and Relevance Feedback Learning Algorithms for Content-Based Mammogram Retrieval
In recent years a large number of digital mammograms have been generated in hospitals and breast screening centers. To assist diagnosis through indexing those mammogram databases, we proposed a content-based image retrieval framework along with a novel feature extraction technique for describing the degree of calcification phenomenon revealed in the mammograms and six relevance feedback learnin...
متن کاملUltra-Fast Image Reconstruction of Tomosynthesis Mammography Using GPU
Digital Breast Tomosynthesis (DBT) is a technology that creates three dimensional (3D) images of breast tissue. Tomosynthesis mammography detects lesions that are not detectable with other imaging systems. If image reconstruction time is in the order of seconds, we can use Tomosynthesis systems to perform Tomosynthesis-guided Interventional procedures. This research has been designed to study u...
متن کاملContent based mammogram retrieval using Gray Level Aura Matrix
Diagnosis of breast cancer in mammograms is also for specialists a difficult and error-prone task. A good opportunity to support radiologists in their decision is to find similar mammograms out of a database to compare the current case with past cases. In this work a complete content based image retrieval (CBIR) system for mass and calcification class mammograms has been implemented under usage...
متن کاملSteganography Scheme Based on Reed-Muller Code with Improving Payload and Ability to Retrieval of Destroyed Data for Digital Images
In this paper, a new steganography scheme with high embedding payload and good visual quality is presented. Before embedding process, secret information is encoded as block using Reed-Muller error correction code. After data encoding and embedding into the low-order bits of host image, modulus function is used to increase visual quality of stego image. Since the proposed method is able to embed...
متن کامل