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The use of computer technology in medical sciences is spreading with technology. The use of computers especially for imaging has become a third eye for physicians. In orthopedic surgeons, after simple roentgenograms for fracture detection, the use of computerized tomography and magnetic resonance has provided great convenience in the detection of fracture, typing, and therefore the appropriate treatment...
The accurate detection of the border surrounding the apical lesions observed in cone-beam Computed Tomography (CT) images is very important for the accurate calculation of the features of these lesions. This study describes a semi-automatic hybrid segmentation method that will be used to determine the limits of apical lesions observed in three-dimensional (3D) KIBT images. The apical cyst and tumor...
Computer-assisted diagnosis (CAD) studies on medical images have gained momentum recently. The studies in this area facilitates the work of medical specialists and reduces the time cost. In this study, meniscus segmentation and meniscus tears were performed on 10 different knee MR images in the 3-D DESS standard obtained on the sagittal plane. The morphological operations used in image processing...
Rising of deep learning methodologies draws huge attention to their application in image processing and classification. Catching up the trends, this study briefly presents state-of-the-art of deep learning applications in medical imaging interfered with achievements of blood vessel segmentation methods in neurosensory retinal fundus images. Successful segmentation based on deep learning offers advantage...
From the preoperative partial nephrectomy planning perspective, it is essential to expose separately different kidney structures and to analyze their mutual topological relations. Only then, the identification of possible conflicts prior to surgical intervention can be facilitated. To enable this, we propose a segmentation frameworks for renal vascular tree, kidney and pelvicalyceal system from corresponding...
Lesion localization is the first and most important step in the development of a melanoma detection system. Skin lesions show distinct color variations as they evolve from benign to malignant one. The use of different color spaces can provide the best discriminative information of lesions embedded in a particular color channel and used in efficient segmentation of a digital image. A simple and efficient...
Ability to clearly delineate the nuclei of microscopic cancer cells is crucial to the accuracy and efficiency of image-based approaches to cancer diagnosis and treatment. Oftentimes, however, such cells contain overlapped (or touched) nuclei. The study proposed in this work presents a hybrid trichotomic technique that combines the Gram-Schmidt method (GSM), handling of relevant geometric features...
Nowadays computer-aided medical systems has become widespread. These systems assist the scientists in the medical field with diagnosis and treatment. In the same vein, in this study detection of medial meniscus from MR images of the knee is performed automatically. Knee MR images used in this study were obtained from Osteoarthritis initiative. 75% of MR images were used for training, while the remainder...
Cervical cancer is the second most common cancer in women world-wide. The accuracy of colposcopy is highly dependent on the physicians individual skills. In expert hands, colposcopy has been reported to have a high sensitivity (96%) and a low specificity (48%) when differentiating abnormal tissues. This leads to a significant interest to activities aimed at the new diagnostic systems and new automatic...
The great achievements in both advanced optical coherence tomography (OCT) technique and computational methods contribute an undeniable tools in clinical diagnosis, especially in ophthalmological diseases diagnosis. Motived to catch up the state of art, the contemporary OCT image segmentation methods widely applied are reviewed and systematically summarized.
Cancer has grown universally as a disease in recent years and it has proven to be the major cause of fatality in humans. The main focal point in this paper is on leukemia - a specific type of blood cancer. The disclosure of leukemia is done with the help of examination of the physical properties of the cells present in the bone marrow smear. This paper introduces peculiar detection of leukemia using...
The differential count and analysis of blood cells in microscope images can provide useful information concerning the health of patients. There are three major blood cell types, namely, erythrocytes (RBCs), leukocytes (WBCs), and platelets. Automated blood cell analysers can provide RBCs, WBCs and platelets count but the presence of abnormal cells could affect the cells counting, that should be checked...
Medical images are being utilized progressively inside the healthcare services for diagnosis, guiding treatment, planning treatment and checking illness progression. In fact, medical imaging chiefly processes uncertain, lost, vague, complementary, conflicting, redundant contradictory, distorted information and data has powerful structural character. As a general approach, the comprehension of any...
Many algorithms for video stabilization have been proposed so far. However, not many digital video stabilization procedures for endoscopic videos are discussed. Endoscopic videos contain immense shakes and distortions as a result of some internal factors like body movements or secretion of body fluids as well as external factors like manual handling of endoscopic devices, introduction of surgical...
Segmentation of the whole liver region from computed tomography (CT) image is the first step in the computer-aided diagnosis for liver disease. In this paper, we propose a new method for segmenting liver region from 3D CT images of abdomen using enhanced Otsu method. Our algorithm uses Otsu method with some improvements to construct intensity model and shape model for liver. First, the 3D CT image...
This paper presents a method for segment and detects the boundary of different breast tissue regions in mammograms by using dynamic K-means clustering algorithm and Seed Based Region Growing (SBRG) techniques. Firstly, the K-means clustering is applied for dynamically and automatically generated the seeds points and determines the thresholds' values for each region. Secondly, the region growing algorithm...
Liver cancer (Hepatocellular carcinoma (HCC)) is considered one of the life threatening diseases that causes death. Early detection of HCC is considered as alive saving process. One of the important tools that helps in the early detection of HCC is image processing. This paper introduces a new size selection region growing based segmentation algorithm for highly accurate liver extraction from CT images...
Detection of implanted iodine-125 seeds in postoperative CT is a necessary step for evaluating the output of seed implantation brachytherapy of lung tumor. In this paper, we propose a semi-automated method to detect implanted seeds in postoperative lung CT. Three main steps are included in our approach. Firstly, the ROI (Region Of Interest) containing all seeds is extracted from the original image...
In histopathology images, there often exists several Nuclei overlapped with each other which causes difficulty to automatic nuclei segmentation. As we all know, watershed algorithm has been widely employed in image segmentation. But the limitation of watershed segmentation is sensitive to noise and can lead to serious over-segmentation. In this paper, we present an improved watershed transformation...
Image segmentation plays a crucial role in breast ultrasound (BUS) for breast cancer detection. However, due to the heavy speckle noise, low contrast and shadowing effects of BUS images, it's a challenging task to develop an accurate and robust segmentation algorithm. In this paper, we present a novel algorithm for breast ultrasound image segmentation which is based on hybrid of level set and graph...
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