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Abnormality Detection from Multispectral Brain MRI using Multiresolution Independent Component Analysis
"... Multispectral approach to brain MRI analysis has shown great advance recently in pathology and tissue analysis. However, poor performance of the feature extraction and classification techniques involved in it discourages radiologists to use it in clinical applications. Transform based feature extrac ..."
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Multispectral approach to brain MRI analysis has shown great advance recently in pathology and tissue analysis. However, poor performance of the feature extraction and classification techniques involved in it discourages radiologists to use it in clinical applications. Transform based feature extraction methods like Independent Component Analysis (ICA) and its variants have contributed a lot in this research field. But these global transforms often fails in extraction of local features like small lesions from clinical cases and noisy data. Feature extraction part of the recently introduced Multiresolution Independent Component Analysis (MICA) algorithm in microarray classification is proposed in this work to resolve this issue. Effectiveness of the algorithm in MRI analysis is demonstrated by training and classification with Support Vector Machines (SVM). Both synthetic and real abnormal data from T1-weighted, T2-weighted, proton density, fluid-attenuated inversion recovery and diffusion weighted MRI sequences are considered for detailed evaluation of the method. Tanimoto index, sensitivity, specificity and accuracy of the classified results are measured and analyzed for brain abnormalities, affected white matter and gray matter tissues
DOCTOR OF SCIENCES OF ETH ZURICH (Dr. sc. ETH Zurich)
, 2014
"... born on 18.02.1985 citizen of Italy accepted on the recommendation of ..."
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An Automatic Image Registration Algorithm for Tracking Moving Objects in Low-Resolution Video
"... Abstract- We propose an automatic image registration algorithm for tracking moving objects in low-resolution videos. The algorithm uses SIFT keypoints to identify matching stationary points in the input frame and the base frame. The best set of matching stationary points is used to create a spatial ..."
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Abstract- We propose an automatic image registration algorithm for tracking moving objects in low-resolution videos. The algorithm uses SIFT keypoints to identify matching stationary points in the input frame and the base frame. The best set of matching stationary points is used to create a spatial transform to register the points on the moving objects in the input frame to the base frame. We examined two probabilistic methods and one deterministic method of identifying the stationary points with two different fitness measures (Euclidean and Mahalanobis) and two spatial transforms (affine and projective). Our experiments on two low-resolution videos indicate that our algorithm performs better using the affine transform than the projective transform. However, the differences in average pixel error between the methods of determining stationary points and fitness measures are statistically insignificant. Therefore, which one to use depends on the execution speed and confidence interval required for the application.
1Precision Engineering, to appear. Registration of Infrared Transmission Images Using Squared-Loss Mutual Information
"... Infrared light allows us to measure the inner structure of opaque samples such as a semi-conductor. In this paper, we propose a method of registering multiple infrared transmission images obtained from different layers of a sample for 3D reconstruction. Since an infrared transmission image obtained ..."
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Infrared light allows us to measure the inner structure of opaque samples such as a semi-conductor. In this paper, we propose a method of registering multiple infrared transmission images obtained from different layers of a sample for 3D reconstruction. Since an infrared transmission image obtained from one layer is contaminated with defocused images coming from other layers, registration with a standard similarity metric such as the squared error and the cross correlation does not perform well. To cope with this problem, we propose to use the squared-loss mutual information as an alternative similarity measure for registration, which is more robust against noise than ordinary mutual information. The practical usefulness of the proposed method is demonstrated in simulated and actual experiments.
THÈSE Délivrée par L’Insitut National des Sciences Appliquées de Lyon
"... Multiparametric organ modeling for shape statistics and simulation procedures. ..."
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Multiparametric organ modeling for shape statistics and simulation procedures.
Image Registration using Blur Invariants in Wavelet Domain
"... Image registration is an important step in all image analysis and it performs the operation of overlaying images of the alike picture taken at various times, from various viewpoints, and/or by various sensors. The wavelet domain provides invariant that are centrally symmetric to blur. Blur invariant ..."
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Image registration is an important step in all image analysis and it performs the operation of overlaying images of the alike picture taken at various times, from various viewpoints, and/or by various sensors. The wavelet domain provides invariant that are centrally symmetric to blur. Blur invariants are constructed from different wavelet function. Template image is chosen in the degraded images using similarity the template image is matched with the original image. Using Daubuchies wavelet functions the images are accurately registered, even in the severely degraded images compared to the spatial domain blur invariants which may result in misfocus registration of an image. Key words
Semi-automatic Landmark Point Annotation for Geometric Morphometrics
"... Background: In previous work, the authors described a software package for the digitisation of 3D landmarks for use in geometric morphometrics. In this paper, we describe extensions to this software that allow semi-automatic location of 3D landmarks, given a database of manually annotated training i ..."
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Background: In previous work, the authors described a software package for the digitisation of 3D landmarks for use in geometric morphometrics. In this paper, we describe extensions to this software that allow semi-automatic location of 3D landmarks, given a database of manually annotated training images. Multi-stage registration was applied to align image patches from the database to a query image, and the results from multiple database images were combined using an array-based voting scheme. The software automatically highlighted points that had been located with low confidence, allowing manual correction. Results: Evaluation was performed on micro-CT images of rodent skulls for which two independent sets of manual landmark annotations had been performed. This allowed assessment of landmark ac-curacy in terms of both the absolute distance between manual and automatic annotations, and the repeatability of manual and automatic annotation. Automatic annotation attained accuracies equiv-alent to those achievable through manual annotation by an expert for 80 % of the points in a typical landmark annotation process, with significantly higher repeatability. Conclusions: Whilst user input was required to produce the training data and in a final error cor-
1 Image Stitching based on Feature Extraction Techniques: A Survey
"... Image stitching (Mosaicing) is considered as an active research area in computer vision and computer graphics. Image stitching is concerned with combining two or more images of the same scene into one high resolution image which is called panoramic image. Image stitching techniques can be categorize ..."
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Image stitching (Mosaicing) is considered as an active research area in computer vision and computer graphics. Image stitching is concerned with combining two or more images of the same scene into one high resolution image which is called panoramic image. Image stitching techniques can be categorized into two general approaches: direct and feature based techniques. Direct techniques compare all the pixel intensities of the images with each other, whereas feature based techniques aim to determine a relationship between the images through distinct features extracted from the processed images. The last approach has the advantage of being more robust against scene movement, faster, and has the ability to automatically discover the overlapping relationships among an unordered set of images. The purpose of this paper is to present a survey about the feature based image stitching. The main components of image stitching will be described. A framework of a complete image stitching system based on feature based approaches will be introduced. Finally, the current challenges of image stitching will be discussed.
Registration of Infrared Transmission Images Using Squared-Loss Mutual Information
"... Infrared light allows us to measure the inner structure of opaque samples such as a semi-conductor. In this paper, we propose a method of registering multiple infrared transmission images obtained from different layers of a sample for 3D reconstruction. Since an infrared transmission image obtained ..."
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Infrared light allows us to measure the inner structure of opaque samples such as a semi-conductor. In this paper, we propose a method of registering multiple infrared transmission images obtained from different layers of a sample for 3D reconstruction. Since an infrared transmission image obtained from one layer is contaminated with defocused images coming from other layers, registration with a standard similarity metric such as the squared error and the cross correlation does not perform well. To cope with this problem, we propose to use the squared-loss mutual information as an alternative similarity measure for registration, which is more robust against noise than ordinary mutual information. The practical usefulness of the proposed method is demonstrated in simulated and actual experiments.
