42 research outputs found
Mengenal pasti tahap pengetahuan pelajar tahun akhir Ijazah Sarjana Muda Kejuruteraan di KUiTTHO dalam bidang keusahawanan dari aspek pengurusan modal
Malaysia ialah sebuah negara membangun di dunia. Dalam proses pembangunan
ini, hasrat negara untuk melahirkan bakal usahawan beijaya tidak boleh dipandang
ringan. Oleh itu, pengetahuan dalam bidang keusahawanan perlu diberi perhatian
dengan sewajarnya; antara aspek utama dalam keusahawanan ialah modal. Pengurusan
modal yang tidak cekap menjadi punca utama kegagalan usahawan. Menyedari hakikat
ini, kajian berkaitan Pengurusan Modal dijalankan ke atas 100 orang pelajar Tahun
Akhir Kejuruteraan di KUiTTHO. Sampel ini dipilih kerana pelajar-pelajar ini akan
menempuhi alam pekeijaan di mana mereka boleh memilih keusahawanan sebagai satu
keijaya. Walau pun mereka bukanlah pelajar dari jurusan perniagaan, namun mereka
mempunyai kemahiran dalam mereka cipta produk yang boleh dikomersialkan. Hasil
dapatan kajian membuktikan bahawa pelajar-pelajar ini berminat dalam bidang
keusahawanan namun masih kurang pengetahuan tentang pengurusan modal
terutamanya dalam menentukan modal permulaan, pengurusan modal keija dan caracara
menentukan pembiayaan kewangan menggunakan kaedah jualan harian. Oleh itu,
satu garis panduan Pengurusan Modal dibina untuk memberi pendedahan kepada
mereka
2D Reconstruction of Small Intestine's Interior Wall
Examining and interpreting of a large number of wireless endoscopic images
from the gastrointestinal tract is a tiresome task for physicians. A practical
solution is to automatically construct a two dimensional representation of the
gastrointestinal tract for easy inspection. However, little has been done on
wireless endoscopic image stitching, let alone systematic investigation. The
proposed new wireless endoscopic image stitching method consists of two main
steps to improve the accuracy and efficiency of image registration. First, the
keypoints are extracted by Principle Component Analysis and Scale Invariant
Feature Transform (PCA-SIFT) algorithm and refined with Maximum Likelihood
Estimation SAmple Consensus (MLESAC) outlier removal to find the most reliable
keypoints. Second, the optimal transformation parameters obtained from first
step are fed to the Normalised Mutual Information (NMI) algorithm as an initial
solution. With modified Marquardt-Levenberg search strategy in a multiscale
framework, the NMI can find the optimal transformation parameters in the
shortest time. The proposed methodology has been tested on two different
datasets - one with real wireless endoscopic images and another with images
obtained from Micro-Ball (a new wireless cubic endoscopy system with six image
sensors). The results have demonstrated the accuracy and robustness of the
proposed methodology both visually and quantitatively.Comment: Journal draf
Distributed-memory large deformation diffeomorphic 3D image registration
We present a parallel distributed-memory algorithm for large deformation
diffeomorphic registration of volumetric images that produces large isochoric
deformations (locally volume preserving). Image registration is a key
technology in medical image analysis. Our algorithm uses a partial differential
equation constrained optimal control formulation. Finding the optimal
deformation map requires the solution of a highly nonlinear problem that
involves pseudo-differential operators, biharmonic operators, and pure
advection operators both forward and back- ward in time. A key issue is the
time to solution, which poses the demand for efficient optimization methods as
well as an effective utilization of high performance computing resources. To
address this problem we use a preconditioned, inexact, Gauss-Newton- Krylov
solver. Our algorithm integrates several components: a spectral discretization
in space, a semi-Lagrangian formulation in time, analytic adjoints, different
regularization functionals (including volume-preserving ones), a spectral
preconditioner, a highly optimized distributed Fast Fourier Transform, and a
cubic interpolation scheme for the semi-Lagrangian time-stepping. We
demonstrate the scalability of our algorithm on images with resolution of up to
on the "Maverick" and "Stampede" systems at the Texas Advanced
Computing Center (TACC). The critical problem in the medical imaging
application domain is strong scaling, that is, solving registration problems of
a moderate size of ---a typical resolution for medical images. We are
able to solve the registration problem for images of this size in less than
five seconds on 64 x86 nodes of TACC's "Maverick" system.Comment: accepted for publication at SC16 in Salt Lake City, Utah, USA;
November 201
Geo-correction of high-resolution imagery using fast template matching on a GPU in emergency mapping contexts
The increasing availability of satellite imagery acquired from existing and new sensors allow a wide variety of new applications that depend on the use of diverse spectral and spatial resolution data sets. One of the pre-conditions for the use of hybrid image data sets is a consistent geo-correction capacity. We demonstrate how a novel fast template matching approach implemented on a Graphics Processing Unit (GPU) allows us to accurately and rapidly geo-correct imagery in an automated way. The key difference with existing geo-correction approaches, which do not use a GPU, is the possibility to match large source image segments (8192 by 8192 pixels) with relatively large templates (512 by 512 pixels). Our approach is sufficiently robust to allow for the use of various reference data sources. The need for accelerated processing is relevant in our application context, which relates to mapping activities in the European Copernicus emergency management service. Our new method is demonstrated over an area North-West of Valencia (Spain) for a large forest fire event in July 2012. We use DEIMOS-1 and RapidEye imagery for the delineation of burnt fire scar extent. Automated geo-correction of each full resolution image sets takes approximately 1 minute. The reference templates are taken from the TerraColor data set and the Spanish national ortho-imagery data base, through the use of dedicate web map services (WMS). Geo-correction results are compared to the vector sets derived in the related Copernicus emergency service activation request.JRC.G.2-Global security and crisis managemen
An accelerated shape based segmentation approach adopting the pattern search optimizer
AbstractAll known solutions of the shape based segmentation problem are slower than real-time application requirements. In this paper, the problem is formulated as a global optimization problem for an energy objective function with several constraints. This formulation allows the use of the global optimization solvers as a solution. However, this solution will be slow as it requires the evaluation of the objective function for several thousand times. The objective function computation is one of the critical factors that affect the time needed to reach a solution. The authors implemented two accelerated parallel versions of the solution that integrates the objective function and the pattern search solver. The first uses a GPU accelerated implementation of the objective function and the second uses a CPU parallel version which is executed on several processors/cores. The results of the proposed solution show that the GPU version has substantial speed compared to other approaches
Parallel Computing of Patch-Based Nonlocal Operator and Its Application in Compressed Sensing MRI
Magnetic resonance imaging has been benefited from compressed sensing in improving imaging speed. But the computation time of compressed sensing magnetic resonance imaging (CS-MRI) is relatively long due to its iterative reconstruction process. Recently, a patch-based nonlocal operator (PANO) has been applied in CS-MRI to significantly reduce the reconstruction error by making use of self-similarity in images. But the two major steps in PANO, learning similarities and performing 3D wavelet transform, require extensive computations. In this paper, a parallel architecture based on multicore processors is proposed to accelerate computations of PANO. Simulation results demonstrate that the acceleration factor approaches the number of CPU cores and overall PANO-based CS-MRI reconstruction can be accomplished in several seconds
Image Registration - Application in ophthalmology and ultrasonography
Registrace medicínských obrazů je v dnešních dnech široce používaná, ale zároveň je i jednou z oblastí zájmu vědeckého výzkumu. Stále nové a vylepšené zobrazovací systémy si žádají stále lepší a výkonnější metody registrace obrazu. Takovou oblastí je i kontrastní ultrazvukové zobrazování. Díky časové proměnlivému kontrastu v obraze, nízkému poměru signál/šum a specifickému šumu typu spekle je registrace ultrazvukových obrazu velice náročná. Dalším problémem je hodnocení kvality registrace. V této dizertační práci je představena metoda registrace ultrazvukových kontrastních sekvencí založena na automatické fragmentaci sekvence do podsekvencí. Následně jsou registrovány obrazy s podobnými vlastnostmi. Dále je představena nová metoda pro hodnocení kvality registrace na základě porovnání perfuzních modelů. Metoda registrace i hodnocení byla testována jak na datech získaných za pomocí fantomu, tak i na reálných pacientských datech. Výsledky pak byly porovnány se standardními metodami publikovanými v odborných článcích. Druhá menší část práce je tvořena ukázkami aplikací různých registračních metod v oftalmologii a návrhy na jejich zlepšení. Jedná se o oblast zobrazovacích systému, kde se registračních metod široce využívá. Kromě jasových registračních metod zde nachází velké uplatnění metody registrace založené na detekci významných bodů. Představené registrační přístupy tak směřují především k detekci těchto významných bodů a stanovení jejich vzájemných korespondencí v jednotlivých obrazech.Image registration is widely used in clinical practice. However image registration and its~evaluation is still challenging especially with regards to new possibilities of various modalities. One of these areas is contrast-enhanced ultrasound imaging. The time-dependent image contrast, low signal-to-noise ratio and specific speckle pattern make preprocessing and image registration difficult. In this thesis a method for registration of images in ultrasound contrast-enhanced sequences is proposed. The method is based on automatic fragmentation into image subsequences in which the images with similar characteristics are registered. The new evaluation method based on comparison of perfusion model is proposed. Registration and evaluation method was tested on a flow phantom and real patient data and compared with a standard methods proposed i literature. The second part of this thesis contains examples of application of image registration in~ophthalmology and proposition for its improvement. In this area the image registration methods are widely used, especially landmark based image registration method. In this thesis methods for landmark detection and its correspondence estimation are proposed.