A comparison of edge detection methods for segmentation of skin lesions in mobile-phone-quality images

The world is faced with a rapidly increasing number of skin cancers every year. Melanoma is the most deadly type of skin cancer though it can be treated if it has been detected at an early stage. However, there is a shortage of dermatologists in rural areas. The increasing number of camera phones, together with improved coverage in rural areas gives some potential for tele-dermatology, whereby people with no local access to a dermatologist can send images of suspicious skin lesions to an expert for assessment. Merely relaying images to a human expert solves only part of the problem, there is still an acute shortage of experts whose time is limited. Computer Assisted Diagnosis (CADi) of lesions promises to reduce the workload of dermatologists by acting as an assistant. Current skin lesion CADi systems employ algorithms that are designed to run on a computer at a clinic. These clinic-based systems are limited when it comes to te/e-dermatology as they rely on a suitable quality image being sent in, and need to process a large number of arriving images. An alternative to this process, afforded by the growing capabilities of mobile phones, is to do some of the CADi processing on the phone which was used to take the image. This has the potential advantage that images can be evaluated for quality on the patient\u27s side, making it more convenient to take another image, rather than waiting for the clinic\u27s assessment. Distributing the processing to the patient\u27s phone also eases the workload on the clinic\u27s machine. The first step towards implementing skin lesion CADi is the segmentation of lesions from the image background; therefore for a mobile phone to perform CADi it is a pre-requisite that it would be able to perform this step. The study seeks to determine, for an existing skin lesion segmentation algorithm, whether it is practical to adapt for mobile phone use given the limitations of the mobile camera\u27s low resolution. The chosen algorithm depends on an edge detection step, and so an investigation will be made into edge detectors. Edge detectors are sensitive to their parameters, pixel size and lighting conditions - thus the parameters published for clinic-based systems which rely on high resolution cameras and custom lighting can not be expected ideal for mobile phone use. Experiments have shown that the approach from Xu et. al. (1999) can only apply on some types of images, which have unique background colour and distinctive from the lesion (foreground) colour

Boundaries and Topological Algorithms

This thesis develops a model for the topological structure of situations. In this model, the topological structure of space is altered by the presence or absence of boundaries, such as those at the edges of objects. This allows the intuitive meaning of topological concepts such as region connectivity, function continuity, and preservation of topological structure to be modeled using the standard mathematical definitions. The thesis shows that these concepts are important in a wide range of artificial intelligence problems, including low-level vision, high-level vision, natural language semantics, and high-level reasoning

Radial Basis Functions: Biomedical Applications and Parallelization

Radial basis function (RBF) is a real-valued function whose values depend only on the distances between an interpolation point and a set of user-specified points called centers. RBF interpolation is one of the primary methods to reconstruct functions from multi-dimensional scattered data. Its abilities to generalize arbitrary space dimensions and to provide spectral accuracy have made it particularly popular in different application areas, including but not limited to: finding numerical solutions of partial differential equations (PDEs), image processing, computer vision and graphics, deep learning and neural networks, etc. The present thesis discusses three applications of RBF interpolation in biomedical engineering areas: (1) Calcium dynamics modeling, in which we numerically solve a set of PDEs by using meshless numerical methods and RBF-based interpolation techniques; (2) Image restoration and transformation, where an image is restored from its triangular mesh representation or transformed under translation, rotation, and scaling, etc. from its original form; (3) Porous structure design, in which the RBF interpolation used to reconstruct a 3D volume containing porous structures from a set of regularly or randomly placed points inside a user-provided surface shape. All these three applications have been investigated and their effectiveness has been supported with numerous experimental results. In particular, we innovatively utilize anisotropic distance metrics to define the distance in RBF interpolation and apply them to the aforementioned second and third applications, which show significant improvement in preserving image features or capturing connected porous structures over the isotropic distance-based RBF method. Beside the algorithm designs and their applications in biomedical areas, we also explore several common parallelization techniques (including OpenMP and CUDA-based GPU programming) to accelerate the performance of the present algorithms. In particular, we analyze how parallel programming can help RBF interpolation to speed up the meshless PDE solver as well as image processing. While RBF has been widely used in various science and engineering fields, the current thesis is expected to trigger some more interest from computational scientists or students into this fast-growing area and specifically apply these techniques to biomedical problems such as the ones investigated in the present work

Impact of varied low resolution phantoms on intensity modulated proton therapy dose distributions

The primary purpose of this thesis is to discuss the usefulness of image segmentation techniques in creating accurate proton dose distribution plans. The calculation of the proton dose distribution has to take into account the material (tissue, bone, brain) in the treatment area of the patients body

Sorotan histeria massa remaja Muslim di Malaysia

Histeria merupakan permasalahan sosial masyarakat yang sering didengari berlaku dalam komuniti. Gejala histeria yang berlaku sama ada secara individu atau kumpulan menunjukkan terdapat tekanan dalam kelompok atau mangsa yang membawa kepada ledakan psikologi yang ekstrim dan di luar kawalan. Histeria yang berlaku khusus dalam kalangan remaja di Malaysia kebanyakannya terjadi secara beramai-ramai atau berkumpulan. Gejala ini dikenali sebagai histeria massa atau histeria epidemik iaitu cetusan histeria yang melibatkan sekumpulan individu yang berkongsi keadaan tertekan dan emosi yang saling berhubung antara satu sama lain. Justeru dengan melihat kepada senario yang berlaku artikel ini ditulis untuk mengupas isu histeria massa dan menyoroti fenomena histeria dalam kalangan remaja Muslim di Malaysia. Kupasan isu ini menggunakan kaedah analisis kandungan dengan cara meneliti dokumen dan artikel berkaitan untuk mengenal pasti gejala histeria massa dalam kalangan remaja. Rumusan perbincangan mendapati histeria massa dalam kalangan remaja di Malaysia kebanyakannya bercorak mass motor hysteria (histeria massa motor) dengan orientasi tingkah laku ceraian (dissociative), iaitu tingkah laku fizikal ekstrim berbanding di Barat yang sering berbentuk mass anxiety hysteria (histeria massa kebimbangan

Toward color image segmentation in analog VLSI: Algorithm and hardware

Standard techniques for segmenting color images are based on finding normalized RGB discontinuities, color histogramming, or clustering techniques in RGB or CIE color spaces. The use of the psychophysical variable hue in HSI space has not been popular due to its numerical instability at low saturations. In this article, we propose the use of a simplified hue description suitable for implementation in analog VLSI. We demonstrate that if theintegrated white condition holds, hue is invariant to certain types of highlights, shading, and shadows. This is due to theadditive/shift invariance property, a property that other color variables lack. The more restrictive uniformly varying lighting model associated with themultiplicative/scale invariance property shared by both hue and normalized RGB allows invariance to transparencies, and to simple models of shading and shadows. Using binary hue discontinuities in conjunction with first-order type of surface interpolation, we demonstrate these invariant properties and compare them against the performance of RGB, normalized RGB, and CIE color spaces. We argue that working in HSI space offers an effective method for segmenting scenes in the presence of confounding cues due to shading, transparency, highlights, and shadows. Based on this work, we designed and fabricated for the first time an analog CMOS VLSI circuit with on-board phototransistor input that computes normalized color and hue

Representing space for practical reasoning

This paper describes a new approach to representing space and time for practical reasoning, based on space-filling cells. Unlike R n, the new models can represent a bounded region of space using only finitely many cells, so they can be manipulated directly. Unlike Z n, they have useful notions of function continuity and region connectedness. The topology of space is allowed to depend on the situation being represented, accounting for sharp changes in function values and lack of connectedness across object boundaries. Algorithms based on this model of space are neither purely region-based nor purely boundary-based, but a blend of the two. This new style of algorithm design is illustrated by a new program for finding edges in grey-scale images. Although the program is based on a relatively conventional second directional difference operator, it can detect fine texture in the presence of camera noise, produce connected boundaries around sharp corners, and return thin boundaries without "feathering. " New algorithms are presented for combining directional differences, suppressing the effects of camera noise, reconstructing image intensities from the second difference values and merging results from different scales (including suppression of spurious boundaries in staircase patterns).