- Presenting Greedy-Linear Algorithm for Automatic Generation of Quantum Circuits’ Layout
March 10, 2011
If there was a quantum computer, the most complicated encryption would be decrypted less than a second. The reason should be searched in enormous throughput and fast speed of quantum processors. Designs which have been proposed by researchers were done manually by no CAD tools. In this paper, a new algorithm by the name of greedy-linear is proposed to generate quantum circuits automatically. The goal of proposed algorithm is to create shortest paths between quantum gates with less delay. Experimental results indicate greedy-linear algorithm has significant effects in area shrinkage and delay decrease of small circuits.
- Improved Values for Matched Filter Parameters for Blood Vessels Extraction of Retinal Images
May 1, 2011
Detection of retinal vessels has a verity of usage in diagnosing of disease such as diabetic retinopathy, hypertension and glaucoma. The matched filter has the most accuracy among all the methods have been presented. In this method, assuming vessels as a Gaussian curve, all bell-ring models are detected through the image entirely. This paper is focused on new parameters which are presented to increase the accuracy of detection. Experimental results indicate that the accuracy in the proposed filter is much more than previous methods.
- Reducing Packet Overhead in Mobile IPv6
July 12, 2012
Common Mobile IPv6 mechanisms, Bidirectional tunneling and Route optimization, show inefficient packet overhead when both nodes are mobile. Researchers have proposed methods to reduce packet overhead regarding to maintain compatible with standard mechanisms. In this paper, three mechanisms in Mobile IPv6 are discussed to show their efficiency and performance. Following discussion, a new mechanism called Improved Tunneling-based Route Optimization is proposed and due to performance analysis, it is shown that proposed mechanism has less overhead comparing to common mechanisms. Analytical results indicate that Improved Tunneling-based Route Optimization transmits more payloads due to send packets with less overhead.
- Breast Density Classification: a comparison of Different Classification Schemes
Zolfagharnasab H., Cardoso J. S.
StudECE Conference, At Porto, Portugal
Although the density of breasts is not a disease, it can lead to indiscrimination of some diseases, since it is hard for specialists to discern tumours in dense tissues. In this paper, based on tissue density, a mammogram is classified in four ordinal classes. To do this, an ordinal classification method is implemented with two different machine learning methods, SVM and Neural Network. Experimental results indicate that by using preprocessing followed by Support vector regression one attain better results than the other implemented methods.
- 3D Breast Parametric Model for Surgery Planning - a Technical Review
RECPAD Conference, At Lisbon, Portugal
Breast cancer is the most common cancer among females. Two main approaches are used as treatment: mastectomy, in which the cancerous breast is completely removed; and conservative treatment, in which the tumour is removed with margin of healthy tissue. To improve surgical approaches resulting less damage to dynamic shape of breast, it is worth to study the breast model to enable specialists having full comparison between the results of different treatments. The aim of this work is to study 3D reconstruction based on passive and active sensors. Also, it is aimed to study state of the art about parametric models to obtain breast shape. Such parametric model can enhance surgeons experience in order to perform better surgeries and patients to be more confident about the breast shape after treatment.
- Cauchy based matched filter for retinal vessels detection
Journal of Medical Signals and Sensors
In this paper, a novel matched filter based on a new kernel function with Cauchy distribution is introduced to improve the accuracy of the automatic retinal vessel detection compared with other available matched filter-based methods, most notably, the methods built on Gaussian distribution function. Several experiments are conducted to pick the best values of the parameters for the new designed filter, including both Cauchy function parameters as well as the matched filter parameters such as the threshold value. Moreover, the thresholding phase is enhanced with a two-step procedure. Experimental results employed on DRIVE retinal images database confirms that the proposed method has higher accuracy compared with other available matched filter-based methods.
- 3D Reconstruction of Body Parts Using RGB-D Sensors: Challenges from a Biomedical Perspective
3D Body Scanning Technologies Conference, At Lugano, Switzerland
The patient 3D model reconstruction plays an important role in applications such as surgery planning or computer-aided prosthesis design systems. Common methods use either expensive devices or require expert personnel which are not available in every clinic. Thus to make patient-specific modelling more versatile, it is required to develop efficient methods together with feasible devices. Body parts such as head and torso present valid challenges with different degrees of complexity, especially because of the absence of relevant and abundant features.
Considering Microsoft Kinect, it is a low-cost and widely available sensor, which has been successfully applied in medical applications. Since single depth-map acquired by Kinect is often incomplete and noisy, different approaches have been proposed to perform the reconstruction by merging multiple depth-maps, by registering single view point clouds generated form each point cloud. As human body is a non-rigid model, most of previous reconstruction methods using Kinect fail to perform accurate reconstruction since they do not address non-rigid surfaces.
In this paper we present the challenges of using low-cost RGB-D sensors to reconstruct human body. Additionally, we analysed coarse registration stage to understand its impact on the quality of reconstruction on both rigid and non-rigid data. Also comparative research has been performed to study different coarse registration methods such as Spin Image (SI), Curvedness, and Principal Component Analysis (PCA). Studies showed that the quality of reconstruction is directly related to robustness of reconstruction method to the rotational and translation noise. Regarding analytical comparisons, results indicate the positive impression of applying coarse registration on both rigid and non-rigid data. Moreover, evaluations show PCA presents better results among other considered methods. Finally it is shown that down-sampled models present less error.
- Tessellation-based Coarse Registration Method for 3D Reconstruction of the Female Torso
IEEE International Conference on Bioinformatics and Biomedicine, At Belfast, Ireland
The medical procedures related with the Breast Cancer Conservative Treatment (BCCT) have evolved towards the usage of affordable and practical tools, along with the recent inclusion of volumetric information of the breast. A richer three dimensional (3D) model of the female torso allows, for instance, improvement of the evaluation the aesthetic outcome of BCCT and the surgery planning. The standard 3D reconstruction methods often fail to model objects of interest using highly misaligned views. In this work, a Tessellation-based coarse registration method is proposed, based on robust key points extraction from RGB-D data using the Delaunay Triangulation (DT) principle. With this method, it is possible to reconstruct female torso data with detail using only 3 views, in feasible time. Structures such as the nipples and the breast contour were correctly reconstructed and a highly correlated with reference models.