• Refine Query
  • Source
  • Publication year
  • to
  • Language
  • 60
  • 41
  • 30
  • 11
  • 4
  • 3
  • 2
  • 2
  • 2
  • 2
  • 1
  • 1
  • 1
  • 1
  • 1
  • Tagged with
  • 180
  • 120
  • 58
  • 42
  • 38
  • 33
  • 33
  • 31
  • 27
  • 25
  • 23
  • 22
  • 21
  • 21
  • 20
  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
51

Computer Aided Long-Bone Segmentation and Fracture Detection

Donnelley, Martin, martin.donnelley@gmail.com January 2008 (has links)
Medical imaging has advanced at a tremendous rate since x-rays were discovered in 1895. Today, x-ray machines produce extremely high-quality images for radiologists to interpret. However, the methods of interpretation have only recently begun to be augmented by advances in computer technology. Computer aided diagnosis (CAD) systems that guide healthcare professionals to making the correct diagnosis are slowly becoming more prevalent throughout the medical field. Bone fractures are a relatively common occurrence. In most developed countries the number of fractures associated with age-related bone loss is increasing rapidly. Regardless of the treating physician's level of experience, accurate detection and evaluation of musculoskeletal trauma is often problematic. Each year, the presence of many fractures is missed during x-ray diagnosis. For a trauma patient, a mis-diagnosis can lead to ineffective patient management, increased dissatisfaction, and expensive litigation. As a result, detection of long-bone fractures is an important orthopaedic and radiologic problem, and it is proposed that a novel CAD system could help lower the miss rate. This thesis examines the development of such a system, for the detection of long-bone fractures. A number of image processing software algorithms useful for automating the fracture detection process have been created. The first algorithm is a non-linear scale-space smoothing technique that allows edge information to be extracted from the x-ray image. The degree of smoothing is controlled by the scale parameter, and allows the amount of image detail that should be retained to be adjusted for each stage of the analysis. The result is demonstrated to be superior to the Canny edge detection algorithm. The second utilises the edge information to determine a set of parameters that approximate the shaft of the long-bone. This is achieved using a modified Hough Transform, and specially designed peak and line endpoint detectors. The third stage uses the shaft approximation data to locate the bone centre-lines and then perform diaphysis segmentation to separate the diaphysis from the epiphyses. Two segmentation algorithms are presented and one is shown to not only produce better results, but also be suitable for application to all long-bone images. The final stage applies a gradient based fracture detection algorithm to the segmented regions. This algorithm utilises a tool called the gradient composite measure to identify abnormal regions, including fractures, within the image. These regions are then identified and highlighted if they are deemed to be part of a fracture. A database of fracture images from trauma patients was collected from the emergency department at the Flinders Medical Centre. From this complete set of images, a development set and test set were created. Experiments on the test set show that diaphysis segmentation and fracture detection are both performed with an accuracy of 83%. Therefore these tools can consistently identify the boundaries between the bone segments, and then accurately highlight midshaft long-bone fractures within the marked diaphysis. Two of the algorithms---the non-linear smoothing and Hough Transform---are relatively slow to compute. Methods of decreasing the diagnosis time were investigated, and a set of parallelised algorithms were designed. These algorithms significantly reduced the total calculation time, making use of the algorithm much more feasible. The thesis concludes with an outline of future research and proposed techniques that---along with the methods and results presented---will improve CAD systems for fracture detection, resulting in more accurate diagnosis of fractures, and a reduction of the fracture miss rate.
52

Feature extraction based on a tensor image description

Westin, Carl-Fredrik January 1991 (has links)
<p>Feature extraction from a tensor based local image representation introduced by Knutsson in [37] is discussed. The tensor representation keeps statements of structure, certainty of statement and energy separate. Further processing for obtaining new features also having these three entities separate is achieved by the use of a new concept, tensor field filtering. Tensor filters for smoothing and for extraction of circular symmetries are presented and discussed in particular. These methods are used for corner detection and extraction of more global features such as lines in images. A novel method for grouping local orientation estimates into global line parameters is introduced. The method is based on a new parameter space, the Möbius Strip parameter space, which has similarities to the Hough transform. A local centroid clustering algorithm is used for classification in this space. The procedure automatically divides curves into line segments with appropriate lengths depending on the curvature. A linked list structure is built up for storing data in an efficient way.</p> / Ogiltigt nummer / annan version: I publ. nr 290:s ISBN: 91-7870-815-X.
53

Classification of Ground Objects Using Laser Radar Data / Klassificering av markobjekt från laserradardata

Brandin, Martin, Hamrén, Roger January 2003 (has links)
Accurate 3D models of natural environments are important for many modelling and simulation applications, for both civilian and military purposes. When building 3D models from high resolution data acquired by an airborne laser scanner it is de-sirable to separate and classify the data to be able to process it further. For example, to build a polygon model of a building the samples belonging to the building must be found. In this thesis we have developed, implemented (in IDL and ENVI), and evaluated algorithms for classification of buildings, vegetation, power lines, posts, and roads. The data is gridded and interpolated and a ground surface is estimated before the classification. For the building classification an object based approach was used unlike most classification algorithms which are pixel based. The building classifica-tion has been tested and compared with two existing classification algorithms. The developed algorithm classified 99.6 % of the building pixels correctly, while the two other algorithms classified 92.2 % respective 80.5 % of the pixels correctly. The algorithms developed for the other classes were tested with thefollowing result (correctly classified pixels): vegetation, 98.8 %; power lines, 98.2 %; posts, 42.3 %; roads, 96.2 %.
54

Detection Of Airport Runways In Optical Satellite Images

Zongur, Ugur 01 July 2009 (has links) (PDF)
Advances in hardware and pattern recognition techniques, along with the widespread utilization of remote sensing satellites, have urged the development of automatic target detection systems. Automatic detection of airports is particularly essential, due to the strategic importance of these targets. In this thesis, a detection method is proposed for airport runways, which is the most distinguishing element of an airport. This method, which operates on large optical satellite images, is composed of a segmentation process based on textural properties, and a runway shape detection stage. In the segmentation process, several local textural features are extracted including not only low level features such as mean, standard deviation of image intensity and gradient, but also Zernike Moments, Circular-Mellin Features, Haralick Features, as well as features involving Gabor Filters, Wavelets and Fourier Power Spectrum Analysis. Since the subset of the mentioned features, which have a role in the discrimination of airport runways from other structures and landforms, cannot be predicted, Adaboost learning algorithm is employed for both classification and determining the feature subset, due to its feature selector nature. By means of the features chosen in this way, a coarse representation of possible runway locations is obtained, as a result of the segmentation operation. Subsequently, the runway shape detection stage, based on a novel form of Hough Transform, is performed over the possible runway locations, in order to obtain final runway positions. The proposed algorithm is examined with experimental work using a comprehensive data set consisting of large and high resolution satellite images and successful results are achieved.
55

Classification of Ground Objects Using Laser Radar Data / Klassificering av markobjekt från laserradardata

Brandin, Martin, Hamrén, Roger January 2003 (has links)
<p>Accurate 3D models of natural environments are important for many modelling and simulation applications, for both civilian and military purposes. When building 3D models from high resolution data acquired by an airborne laser scanner it is de-sirable to separate and classify the data to be able to process it further. For example, to build a polygon model of a building the samples belonging to the building must be found.</p><p>In this thesis we have developed, implemented (in IDL and ENVI), and evaluated algorithms for classification of buildings, vegetation, power lines, posts, and roads. The data is gridded and interpolated and a ground surface is estimated before the classification. For the building classification an object based approach was used unlike most classification algorithms which are pixel based. The building classifica-tion has been tested and compared with two existing classification algorithms. </p><p>The developed algorithm classified 99.6 % of the building pixels correctly, while the two other algorithms classified 92.2 % respective 80.5 % of the pixels correctly. The algorithms developed for the other classes were tested with thefollowing result (correctly classified pixels): vegetation, 98.8 %; power lines, 98.2 %; posts, 42.3 %; roads, 96.2 %.</p>
56

Hough transforms for shape identification and applications im medical image processing /

Lu, Wei, January 2003 (has links)
Thesis (Ph. D.)--University of Missouri-Columbia, 2003. / Typescript. Vita. Includes bibliographical references (leaves 105-112). Also available on the Internet.
57

Hough transforms for shape identification and applications im medical image processing

Lu, Wei, January 2003 (has links)
Thesis (Ph. D.)--University of Missouri-Columbia, 2003. / Typescript. Vita. Includes bibliographical references (leaves 105-112). Also available on the Internet.
58

Trimačių objektų identifikavimas magnetinio rezonanso vaizduose / Identification of tridimentional objects by magnetic resonance imaging

Laugalys, Vytautas 08 September 2009 (has links)
Vaizdų atpažinimas yra įvairios kilmės vaizdų analizės, apdorojimo, atpažinimo ir atvaizdavimo – rezultatas. Medicinoje gautų vaizdų apdorojimas ir analizė, pagrysti įvairiausiais metodais iš kurių galima sudaryti tinkamą algoritmą atpažinimui. Įvairūs objektai skenuotose (fotografuotose) ar filmuose duomenyse, yra tiesiogiai nematomi, todėl kiekvieno iš jų vizualizavimas turi skirtingus algoritmus. Šiuolaikinė mokslo pažanga biofizikoje ir informatikoje pateikia vis daugiau pagalbos gydytojui pasiekti ir panaudoti naujus mokslo rezultatus, kelti gydimo kokybę. Didelis informacijos perteklius kelia žinių apdorojimo problemą, kurią spręsti galima pateikiant kompiuteriui apdoroti, išskirti informaciją. Magnetinio rezonanso nuotraukos padeda netik pamatyti vidinius organus, bet ir stebėti jų keitimąsi laikui bėgant, tam tikslui turi būti saugomi duomenys apie tiriamą organą. Šis darbas siūlo algoritmus automatiškai selektyviai išskiriančius tiriamus žmogaus vidaus organus. / The classical problem in computer imaging, image processing and machine vision is that of determining whether or not the image data contains some specific object, feature, or activity in 2D, but in 3D there is no method for recognition of the objects. In this paper, I have analyzed how to adjust methods for 3D MR imaging and recognize the objects (human body internal organs).
59

SPHEROID DETECTION IN 2D IMAGES USING CIRCULAR HOUGH TRANSFORM

Chaudhary, Priyanka 01 January 2010 (has links)
Three-dimensional endothelial cell sprouting assay (3D-ECSA) exhibits differentiation of endothelial cells into sprouting structures inside a 3D matrix of collagen I. It is a screening tool to study endothelial cell behavior and identification of angiogenesis inhibitors. The shape and size of an EC spheroid (aggregation of ~ 750 cells) is important with respect to its growth performance in presence of angiogenic stimulators. Apparently, tubules formed on malformed spheroids lack homogeneity in terms of density and length. This requires segregation of well formed spheroids from malformed ones to obtain better performance metrics. We aim to develop and validate an automated imaging software analysis tool, as a part of a High-content High throughput screening (HC-HTS) assay platform, to exploit 3D-ECSA as a differential HTS assay. We present a solution using Circular Hough Transform to detect a nearly perfect spheroid as per its circular shape in a 2D image. This successfully enables us to differentiate and separate good spheroids from the malformed ones using automated test bench.
60

DESIGN OF A GAIT ACQUISITION AND ANALYSIS SYSTEM FOR ASSESSING THE RECOVERY OF MICE POST-SPINAL CORD INJURY

Harr, Casey 01 January 2005 (has links)
Current methods of determining spinal cord recovery in mice, post-directed injury, are qualitative measures. This is due to the small size and quickness of mice. This thesis presents a design for a gait acquisition and analysis system able to capture the footfalls of a mouse, extract position and timing data, and report quantitative gait metrics to the operator. These metrics can then be used to evaluate the recovery of the mouse. This work presents the design evolution of the system, from initial sensor design concepts through prototyping and testing to the final implementation. The system utilizes a machine vision camera, a well-designed walkway enclosure, and image processing techniques to capture and analyze paw strikes. Quantitative results gained from live animal experiments are presented, and it is shown how the measurements can be used to determine healthy, injured, and recovered gait.

Page generated in 0.0423 seconds