Browsing by Department "DKU - Medical Physics Master of Science Program"
Now showing items 1-20 of 33
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A Comparative Study of Radiomics and Deep-Learning Approaches for Predicting Surgery Outcomes in Early-Stage Non-Small Cell Lung Cancer (NSCLC)
(2022)Purpose: To compare radiomics and deep-learning (DL) methods for predicting NSCLC surgical treatment failure. Methods: A cohort of 83 patients undergoing lobectomy or wedge resection for early-stage NSCLC from our institution ... -
A Convolutional Neural Network for SPECT Image Reconstruction
(2022)Purpose: Single photon emission computed tomography (SPECT) is considered as a functional nuclear medicine imaging technique which is commonly used in the clinic. However, it suffers from low resolution and high noise because ... -
A Deep-Learning Method of Automatic VMAT Planning via MLC Dynamic Sequence Prediction (AVP-DSP) Using 3D Dose Prediction: A Feasibility Study of Prostate Radiotherapy Application
(2020)Introduction: VMAT treatment planning requires time-consuming DVH-based inverse optimization process, which impedes its application in time-sensitive situations. This work aims to develop a deep-learning based algorithm, ... -
A Deep-Learning-based Multi-segment VMAT Plan Generation Algorithm from Patient Anatomy for Prostate Simultaneous Integrated Boost (SIB) Cases
(2021)Introduction: Several studies have realized fluence-map-prediction-based DL IMRT planning algorithms. However, DL-based VMAT planning remains unsolved. A main difficult in DL-based VMAT planning is how to generate leaf sequences ... -
A New Method to Investigate RECA Therapeutic Effect
(2020)Introduction: RECA (Radiotherapy Enhanced with Cherenkov photo- Activation) is a novel treatment that induces a synergistic therapeutic effect by combining conventional radiation therapy with phototherapy using the anti-cancer ... -
A novel technique to irradiate surgical scars using dynamic electron arc radiotherapy
(2017)Purpose: The usage of conformal electron beam therapy techniques in treating superficial tumors on uneven surfaces has often lead to undesired outcomes such as non-uniform dose inside the target and a wide penumbra at boundary ... -
A Prospective Method for Selecting the Optimal SPECT Pinhole Trajectory
(2021)AbstractPinhole imaging is a widely used method for high spatial resolution single gamma imaging with a small required field of view (FOV). Many factors affect pinhole imaging: (I) the geometric parameters of the pinhole ... -
A Tool for Approximating Radiotherapy Delivery via Informed Simulation (TARDIS)
(2020)Purpose: The multi-leaf collimator (MLC) is a critical component in intensity modulated radiation therapy (IMRT) and volumetric modulated arc therapy (VMAT). The MLC discrepancies between planned and actual position directly ... -
An Investigation in Quantitative Accuracy in Preablation I-131 Scans: 7-pinhole system compared with single-pinhole system.
(2018)Purpose: Early detection and prevention of differentiated thyroid cancer using thyroidectomy and ablation therapy can reduce disease persistence and recurrence. A preablation I-131 scan performed between the thyroidectomy ... -
An Investigation of Machine Learning Methods for Delta-radiomic Feature Analysis
(2018)Background: Radiomics is a process of converting medical images into high-dimensional quantitative features and the subsequent mining these features for providing decision support. It is conducted as a potential noninvasive, ... -
An Investigation of MR Sequences for Partial Volume Correction in PET Image Reconstruction
(2019)Brain Positron emission tomography (PET) has been widely employed for the clinic diagnosis of Alzheimer's disease (AD). Studies have shown that PET imaging is helpful in differentiating healthy elderly individuals, mild ... -
Automatic Pulmonary Nodule Detection and Localization from Biplanar Chest Radiographs Using Convolutional Neural Network
(2019)Chest x-ray (CXR) is the most common examination in pulmonary nodule detection and an automatic nodule detection algorithm is desirable. Currently, convolutional neural network (CNN) is widely applied in CXR. However, there ... -
Building a patient-specific model using transfer learning for 4D-CBCT augmentation
(2020)Purpose: Four-dimensional cone beam computed tomography (4D-CBCT) has been developed to provide respiratory phase‐resolved volumetric images in aid of image guided radiation therapy (IGRT), especially in SBRT, which requires ... -
Cone Beam Computed Tomography Image Quality Augmentation using Novel Deep Learning Networks
(2019)Purpose: Cone beam computed tomography (CBCT) plays an important role in image guidance for interventional radiology and radiation therapy by providing 3D volumetric images of the patient. However, CBCT suffers from relatively ... -
Deriving Lung Ventilation MAP Directly from Auto Segmented CT Images Using Deep Convolutional Neural Network (CNN)
(2022)Lung cancer has been the most commonly occurring cancer (J. Ferlay, 2018), with the highest fatality rate worldwide. Lung cancer patients undergoing radiation therapy typically experience many side effects. In order to reduce ... -
Development and Evaluation of a Perpendicular Frame-by-frame Patient-specific QA Method for Large VMAT Fields Using the TrueBeam Electronic Portal Imaging System
(2019)Background: The verification of VMAT delivery accuracy is widely performed with measurement-based QA methods and gamma index test evaluation. Having the gantry speed as an element of modulation requires that VMAT QA methods ... -
Effect of Lower-energy Source on the Tumor Representation in Neutron Stimulated Emission Computed Tomography: An Evaluation Study
(2017)Proposed is an investigation into the effect of lower-energy source on the tumor representation of an image acquired by a neutron-based spectroscopic imaging modality, Neutron Stimulated Emission Computed Tomography (NSECT).The ... -
Effect of Radiation and Immune Checkpoint Blockade (ICB) on Tumor Metastasis
(2017)Background: PD-L1 (Programmed Death Ligand 1) is an immune checkpoint molecule that is commonly expressed on the surface of cancer cells. When it interacts with its receptor – the PD-1 molecule, which is commonly expressed ... -
Evaluation of Prone Breast PET/CT Imaging Using Phantoms
(2019)The different patient orientations in breast PET/CT and breast MR imaging, supine versus prone, respectively, cause difficulty in integrating and interpreting the data acquired from these two types of imaging protocols. ... -
Evaluation of the Total Body Irradiation Treatment Planning Using Eclipse
(2019)Purpose: Total Body Irradiation (TBI) is typically performed at extended source-to-skin distance (SSD), and the treatment planning is done by simple point dose calculation based on measurement data. The goal of this study ...
