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The Cholangiocarcinoma (CCA) is the most common in northeast Thailand that is second most common worldwide. The Periductal fibrosis (PDF) ultrasound images can be applied for the CCA surveillance system which increased patient in endemic area of Opisthorchis viverrini (OV). However, the ultrasound images are lack of contrast and a lot of speckle noise. This paper presented the enhanced algorithm of...
We present a Sparse Representation-based Classifier (SRC) that provides superior performance in terms of high Area Under the Receiver Operating Characteristic (ROC) Curve (AUC) in classifying benign and malignant breast lesions captured in ultrasound images. Although such a classifier was proposed for face recognition, it has been proposed in medical diagnosis from ultrasonic images in this work for...
Image denoising is an important in the field of medical image processing and computer vision. Image denoising continues a challenge for researchers because noise removal gives artifacts and the main source for blurring of the images. In this work four different methods are proposed to reduce the image artifacts and noise in the MRI images and also Partial Differential Equations (PDE) is applied to...
This paper introduces a novel procedure to segment retinal vessels using new technique namely Morphological Angular Scale-Space (MASS). Line structuring element is rotated about the seed point to determine the curvature of the vessels thereby ensuring that the components remains connected along vessels segmented. Scale-Space is created by varying the length of the structuring element which gradually...
This paper presents an algorithm for a 3D segmentation of the aorta artery in magnetic resonance images (MRI). The purpose is to project the 3D segmented aorta in the patient's abdomen with an augmented reality (AR) system to help the surgeon in laparoscopic interventions. In order to obtain accurate results in the segmentation process a marker-controlled watershed algorithm is used. Since this method...
The inverse problem of fluorescence diffuse optical tomography (FDOT) is often highly ill-posed, which needs regularization techniques. In this paper, we propose a combined l1-l2-norm regularization method to address the ill-posed FDOT inverse problem. Compared with the traditional Tikhonov regularization, the proposed method is able to effectively remove the noise in the reconstructed image without...
Melanoma can be cured if it is detected early, so early diagnosis is very important in dermatological practice today. Early and non-invasive diagnosis of melanomas can be done by accurate image segmentation of skin lesions. The medical images, while acquisition are generally bound to contain noise. This paper proposes a robust and efficient image segmentation algorithm using LOG edge detector to extract...
This paper presents the evaluation of the effect of noise reduction techniques on the brain Computed Tomography (CT) images. In particular, multiscale geometric denoising methods based on curvelet transform are used and compared with wavelet based methods. The simulated results show that cycle spinning based curvelet transform method outperforms the wavelet based methods not only for the suppression...
Ultrasound imaging is a widely used and safe medical diagnostic technique, due to its noninvasive nature, low cost, real time imaging. However the usefulness of ultrasound imaging is degraded by the presence of signal depended noise known as speckle.. The speckle pattern depends on the structure of the image tissue and various imaging parameters. There are two main purposes for speckle reduction in...
Radiation exposure increases the risk of inducing cancer in a patient when Computed Tomography is performed. Radiologists reduce the radiation dose to minimize the risk of cancer, consequently, noise is introduced in the image, considerably penalizing its quality. To enhance the quality of the image, different noise filters are developed. The filtered noise can be discarded due to its insignificance...
A new approach to SPECT and planar imaging has been proposed which uses neutron-activated tracers in place of traditional radioisotopes. A preliminary experiment was conducted to assess the feasibility of the proposed method. A Rose model-style phantom was imaged using 131I as a proxy for a particular neutron activated isotope with a similar primary photon energy. Poisson noise caused by hydrogen...
Patient motion degrades image quality in medical imaging. Gating can reduce motion artifacts by using part of the acquired data, but can increase noise. Motion-compensated image reconstruction (MCIR) utilizes all collected data with motion information to reduce motion artifacts and noise. Interactions between Poisson log-likelihood and quadratic regularizers lead to nonuniform and anisotropic spatial...
Maps of perfusion and Arterial Transit Time (ATT) can be measured quantitatively using non-invasive Pulsed Arterial Spin Labeling (PASL) techniques. This can be achieved by fitting a kinetic model to magnetization difference data images acquired at multiple inversion times (TI). Here, spatial information is incorporated into a Bayesian estimation method, based on a maximum a posteriori (MAP) criterion,...
Robust tumor activity quantification recently finds application in challenging medical scenarios like early therapy response detection, radiotherapy treatment planning, etc. This paper targets a quantitative comparison of existing state of the art Positron Emission Tomography (PET) volume delineation methodologies. The different methods evaluated include adaptive threshold based, gradient based and...
The channelized Hotelling observer (CHO) has become a widely used approach for evaluating medical image quality, acting as a surrogate for human observers in early-stage research on assessment and optimization of imaging devices and algorithms. Its popularity stems from experiments showing that, when an internal-noise model is introduced, the CHO's detection performance can be tuned to correlate well...
The physical limitations of medical imaging devices together with the adverse effect of measurement noises tend to reduce the resolution and contrast of resulting diagnostic images. As a result, there is a need to preprocess the images before their interpretation by a medical practitioner. The present study is concerned with the case in which the images of interest are degraded by convolutional blur...
The total variation smoothing methods are common in image processing due to its remarkable ability to preserve edges. Its application in medical image reconstruction has also being addressed by several researchers. The corresponding reconstruction algorithms developed, however, either lack considerations of the positivity constraint usually imposed on medical images, or are not flexible enough to...
Magnetic particle imaging (MPI) is a quantitative method for determining the spatial distribution of superparamagnetic nanoparticles in-vivo. It applies various static and dynamic magnetic fields resulting in a spatially dependent particle magnetization characteristic, which can be recorded using receive coils. For spatial encoding, different field topologies were developed, which use either a point-based...
Recently we developed a periodic modeling approach for determining the optical flow in a periodic image sequence, which is demonstrated to be beneficial for noise reduction in motion-compensated 4D reconstruction of cardiac gated images. In this approach, a Fourier harmonic model is used to exploit the temporal continuity and periodicity of the motion field in the sequence. In this work, we further...
Segmenting ultrasound images is a challenging problem where standard unsupervised segmentation methods such as the well-known Chan-Vese method fail. We propose in this paper an efficient segmentation method for this class of images. Our proposed algorithm is based on a semi-supervised approach (user labels) and the use of image patches as data features. We also consider the Pearson distance between...
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