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Bioimaging and Biomedical Optics Commons™
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- Computer Sciences (7)
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- 2D ultrasound (1)
- 3D reconstruction (1)
- Abdominal images (1)
- Anisotropic Diffusion (1)
- Bone age assessment (1)
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- Breast cancer (1)
- Breast cancer detection; Medical image classification; Deep learning; Histopathology images (1)
- Cell recognition (1)
- Computerized axial tomography (CAT) scan (1)
- Computerized tomography (CT) (1)
- Diagnose; Cardiovascular; Visualisation Toolkit; Surface rendering technique; Volume rendering technique (1)
- Diffusivity function (1)
- Distal stent graft-induced new entry (dSINE); Aortic dissection (AoD); Thoracic endovascular aortic repair (TEVAR); Wedge apposition angle; Tortuosity angle (1)
- Edge preservation (1)
- Histogram equalization (1)
- Knee arthritis (1)
- Machine learning (1)
- Magnetic resonance imaging (1)
- Mammography; Histogram clipping; Histogram equalization; Mammogram enhancement; Local contrast (1)
- Medical imaging; Computer-assisted image segmentation; Magnetic resonance imaging; Level set method; 3D image reconstruction (1)
- Neural network (1)
- Resnet-50 (1)
- Screening test (1)
- Speckle-noise reduction (1)
- Surface Rendering technique (1)
- Visual enhancement (1)
- Visualisation toolkit (VTK) (1)
- Visualization toolkit (VTK) (1)
- Volume Rendering technique (1)
Articles 1 - 10 of 10
Full-Text Articles in Bioimaging and Biomedical Optics
An Improved Clipped Sub-Histogram Equalization Technique Using Optimized Local Contrast Factor For Mammogram Image Analysis, Nurshafira Hazim Chan
An Improved Clipped Sub-Histogram Equalization Technique Using Optimized Local Contrast Factor For Mammogram Image Analysis, Nurshafira Hazim Chan
Student Works (2020-2029)
Mammography has been known worldwide as the most common imaging modalities utilized for early detection of breast cancer. The mammographic images produced are in greyscale, however they often produced poor contrast images, non-uniform illumination, and the image often contain artefacts and noise. These limitations can be overcame during the pre-processing stage by improving the image enhancement process. Therefore, in this research an optimized enhancement framework is developed where the local contrast factor is manipulated to preserve details of the image. This technique aims to improve the overall image visibility without altering histogram of the original image, which will affect the …
Biomechanical Analysis Of Distal Stent-Graft-Induced New Entry (Sine) Formation In Aortic Dissection Patients, Tan Wei Ting
Biomechanical Analysis Of Distal Stent-Graft-Induced New Entry (Sine) Formation In Aortic Dissection Patients, Tan Wei Ting
Student Works (2020-2029)
Distal stent graft-induced new entry (dSINE) is a post-treatment complication with a mortality rate of 26.1-28.6% in patients with aortic dissection (AD). dSINE creates a new path for blood flow, leading to the formation of false lumen, aneurysmal expansion, and aortic rupture. These complications necessitate re-intervention in 30-60% patients. In this study, computational approach was used to investigate potential risk factors for dSINE in aortic dissection patients. Patient-specific simulations were performed based on post thoracic endovascular aortic repair (TEVAR) computed tomography images acquired from six patients (3 dSINE and 3 non-dSINE) to analyse the correlation between anatomical characteristics and stress/strain …
Deep Learning-Based Breast Cancer Detection And Classification Using Histopathology Images, Ghulam Murtaza
Deep Learning-Based Breast Cancer Detection And Classification Using Histopathology Images, Ghulam Murtaza
Student Works (2020-2029)
Cancer disease is drastically increasing worldwide over the past few years. Among all types of cancers in women, breast cancer (BrC) is the main cause of abnormal deaths. For a confident diagnosis of BrC, histopathology (Hp) images are usually suggested by the doctors. BrC detection is a diagnostic test for benign (non-cancerous) and malignant (cancerous) breast tumors (BrT). Once the BrT is diagnosed, then it needs to be classified for subtypes of benign and malignant to start specific treatment. Several studies developed BrC detection and classification models using Hp images. However, the existing models required high computational resources, long training …
Three-Dimensional (3d) Reconstruction Of Computer Tomography Cardiac Images Using Visualization Toolkit (Vtk), Mohammad Zahid Zamaludin
Three-Dimensional (3d) Reconstruction Of Computer Tomography Cardiac Images Using Visualization Toolkit (Vtk), Mohammad Zahid Zamaludin
Student Works (2020-2029)
Cardiac study proves to be important to diagnose and treat cardiovascular disease that accounts for 20% of death in the world. Three-dimensional (3D) images of the heart are important to understand its real structure, functions and physical abnormalities occurring in the tissue. The objective of this paper is to reconstruct 3D images from 2D CT Scan slices of the cardiac region of interest using Visualisation Toolkit (VTK). The Visualization Toolkit (VTK) is non-propriety software with state-of-the-art tools for 3D rendering that is easily customizable programming. 3D images are reconstructed using surface rendering technique and volume rendering technique. Volume rendering shows …
Three-Dimensional (3d) Reconstruction Of Computed Tomography (Ct) Abdominal Images Using Visualization Toolkit (Vtk), Mat Saad Afifah Husna
Three-Dimensional (3d) Reconstruction Of Computed Tomography (Ct) Abdominal Images Using Visualization Toolkit (Vtk), Mat Saad Afifah Husna
Student Works (2020-2029)
A computerized tomography (CT) or computerized axial tomography (CAT) scan combines data from several X-raysito produce a detailed image of structures inside the body. CT scans produce 2D of a “slice” or section of the abdomen but the data can also be used to construct 3-dimensional images. However, CT scan unable to accurately represent the internal structure of soft tissues and soft-tissue lesions. Therefore, using the program in Visualization Tool Kit (VTK) is needed to construct a much more clearer 3D image. To reconstruct 3D images from 2D images of a “slice” or section of abdomen which will be resulting …
Three-Dimensional (3d) Reconstruction Of Ultrasound Foetal Images Using Visualisation Toolkit (Vtk), Henry Dusim Grace Anabela
Three-Dimensional (3d) Reconstruction Of Ultrasound Foetal Images Using Visualisation Toolkit (Vtk), Henry Dusim Grace Anabela
Student Works (2020-2029)
Three-dimensional (3D) reconstruction of two-dimensional (2D) ultrasound images has been used for easier analysing of anatomy related to abnormalities. 3D image reconstruction is required as it helps doctors interpret results and assess any defects quickly. Not only does it improve the accuracy of diagnosis, but it also saves a lot of time. In this thesis, 295 slices of 2D ultrasound images of a foetal are used to do 3D reconstruction using surface rendering, volume rendering, and multiplanar rendering technique. A similar software known as 3D Slicer is also used to reconstruct the ultrasound image for comparison purpose. VTK can easily …
Identification Of Microscopy Cell Images By Using Convolutional Neural Network Application, Ajis Norfatin Farisya
Identification Of Microscopy Cell Images By Using Convolutional Neural Network Application, Ajis Norfatin Farisya
Student Works (2020-2029)
Breast cancer has been the major factor of cancer death and the second main cause of women’s deaths in the world. The false positive results of this cancer cell detection during the screening test leads to false treatment and emotional disturbance of the patients. Thus, breast cancer cell lines (MCF7) is used as the microscopy image samples together with the Human Bone Osteosarcoma Epithelial Cells (U2OS), and Human Hepatocyte as control to study the effectiveness of convolutional neural network (CNN) as a method of image recognition. The objectives of this study are to determine the ability of convolutional neural network …
An Improved Bone Age Assessment Using Advanced Image Processing And Deep Learning Approach, Kim Meng Liang
An Improved Bone Age Assessment Using Advanced Image Processing And Deep Learning Approach, Kim Meng Liang
Student Works (2020-2029)
Pediatricians often apply bone age assessment to measure the skeletal maturity of children and to predict the future height. These discrepancies are good indicators for diagnosing growth disorders. Normally, left hand skeletal is employed in this assessment. The low quality of ossification sites of carpals deteriorates the pediatrician’s visibility in inspecting the pertinent radiographic manifestations. This in turn affects the bone age assessment. Therefore, we have to enhance the quality before assessing them. Histogram equalization is one of the contrast enhancement techniques that suit this type of enhancement. Existing histogram equalizations, however, are confronting with problems in preserving the brightness …
Speckle-Noise Reduction In Knee Articular Cartilage Ultrasound Image Using Anisotropic Diffusion, Ali Muhammad Shoaib
Speckle-Noise Reduction In Knee Articular Cartilage Ultrasound Image Using Anisotropic Diffusion, Ali Muhammad Shoaib
Student Works (2020-2029)
Knee arthritis is the most common type of arthritis which effects the people and may cause severe pain to the patient and can lead to joint effusion. Ultrasound (US) imaging is an appropriate and consistent substitute for other imaging techniques like magnetic resonance imaging or X-rays in the investigation or screening of knee injury. Nevertheless, one of the major problems in US images which make the analysis of these images hard is the presence of speckle noise. For the reduction of speckle noise, the performance of the anisotropic method is found much better over other approaches. In removing the speckle …
Level Set Segmentation Of Mr Images For Extraction Of Femur Bone And Tissues, Christina Shanti Nayagam
Level Set Segmentation Of Mr Images For Extraction Of Femur Bone And Tissues, Christina Shanti Nayagam
Student Works (2000-2009)
This research explores a potentially useful segmentation algorithm, known as the level set method. It is suitable for images obtained from the Magnetic Resonance Imaging (MRJ) modality, despite the fact that MR images have low contrast between bone and tissue. The level set method is a numerical technique designed to track the evolution of an interface. The fast marching version of the method is implemented for two-dimensional (2-D) and three-dimensional (3-D) segmentation in this research. Femur segmentation is the main thrust of this thesis, however brain and heart images are also presented. Pre-processing steps are first performed for the 2-0 …