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View article: Optical Flow-Based Extraction of Breathing Signal from Cone Beam CT Projections
Optical Flow-Based Extraction of Breathing Signal from Cone Beam CT Projections Open
Respiratory motion serves as a major challenge during treatment of lung cancer patients using radiotherapy. In this work, an image-based method is presented to extract a respiratory signal directly from Cone Beam CT (CBCT) projections. A d…
View article: Machine Learning-Based Approaches for Breast Density Estimation from Mammograms: A Comprehensive Review
Machine Learning-Based Approaches for Breast Density Estimation from Mammograms: A Comprehensive Review Open
Breast cancer, as of 2022, is the most prevalent type of cancer in women. Breast density—a measure of the non-fatty tissue in the breast—is a strong risk factor for breast cancer that can be estimated from mammograms. The importance of stu…
View article: Can Machine Learning Enhance Intrusion Detection to Safeguard Smart City Networks from Multi-Step Cyberattacks?
Can Machine Learning Enhance Intrusion Detection to Safeguard Smart City Networks from Multi-Step Cyberattacks? Open
Intrusion detection systems are essential for detecting network cyberattacks. As the sophistication of cyberattacks increases, it is critical that defense technologies adapt to counter them. Multi-step attacks, which need several correlate…
View article: Machine Learning-Based X-Ray Projection Interpolation for Improved 4D-CBCT Reconstruction
Machine Learning-Based X-Ray Projection Interpolation for Improved 4D-CBCT Reconstruction Open
Goal: Respiration-correlated cone-beam computed tomography (4D-CBCT) is an X-ray-based imaging modality that uses reconstruction algorithms to produce time-varying volumetric images of moving anatomy over a cycle of respiratory moti…
View article: Predicting the Spread of a Pandemic Using Machine Learning: A Case Study of COVID-19 in the UAE
Predicting the Spread of a Pandemic Using Machine Learning: A Case Study of COVID-19 in the UAE Open
Pandemics can result in large morbidity and mortality rates that can cause significant adverse effects on the social and economic situations of communities. Monitoring and predicting the spread of pandemics helps the concerned authorities …
View article: Investigating the Effect of Patient-Related Factors on Computed Tomography Radiation Dose Using Regression and Correlation Analysis
Investigating the Effect of Patient-Related Factors on Computed Tomography Radiation Dose Using Regression and Correlation Analysis Open
Computed tomography (CT) is a widely utilized diagnostic imaging modality in medicine. However, the potential risks associated with radiation exposure necessitate investigating CT exams to minimize unnecessary radiation. The objective of t…
View article: Machine Learning Based Palm Farming: Harvesting and Disease Identification
Machine Learning Based Palm Farming: Harvesting and Disease Identification Open
In the culturally and economically vital date palm sector of the Arab world, precise assessment of fruit maturity, type, and disease is crucial for optimizing yield, quality, and palm health. This work pioneers a novel paradigm: machine le…
View article: A Hybrid Transfer Learning Approach to Teeth Diagnosis Using Orthopantomogram Radiographs
A Hybrid Transfer Learning Approach to Teeth Diagnosis Using Orthopantomogram Radiographs Open
The rise in the emphasis on oral diseases has elevated the need to automate the diagnostic process of such diseases. Fortunately, the availability of modern computing devices has made the automated diagnosis of teeth readily possible using…
View article: Wireless Capsule Endoscopy Image Classification: An Explainable AI Approach
Wireless Capsule Endoscopy Image Classification: An Explainable AI Approach Open
Deep Learning has contributed significantly to the advances made in the fields of Medical Imaging and Computer Aided Diagnosis (CAD). Although a variety of Deep Learning (DL) models exist for the purposes of image classification in the med…
View article: Regression Analysis between the Different Breast Dose Quantities Reported in Digital Mammography and Patient Age, Breast Thickness, and Acquisition Parameters
Regression Analysis between the Different Breast Dose Quantities Reported in Digital Mammography and Patient Age, Breast Thickness, and Acquisition Parameters Open
Breast cancer is the leading cause of cancer death among women worldwide. Screening mammography is considered the primary imaging modality for the early detection of breast cancer. The radiation dose from mammography increases the patients…
View article: An IoT Machine Learning-Based Mobile Sensors Unit for Visually Impaired People
An IoT Machine Learning-Based Mobile Sensors Unit for Visually Impaired People Open
Visually impaired people face many challenges that limit their ability to perform daily tasks and interact with the surrounding world. Navigating around places is one of the biggest challenges that face visually impaired people, especially…
View article: Microwave Imaging for Early Breast Cancer Detection: Current State, Challenges, and Future Directions
Microwave Imaging for Early Breast Cancer Detection: Current State, Challenges, and Future Directions Open
Breast cancer is the most commonly diagnosed cancer type and is the leading cause of cancer-related death among females worldwide. Breast screening and early detection are currently the most successful approaches for the management and tre…
View article: Exogenous Contrast Agents in Photoacoustic Imaging: An In Vivo Review for Tumor Imaging
Exogenous Contrast Agents in Photoacoustic Imaging: An In Vivo Review for Tumor Imaging Open
The field of cancer theranostics has grown rapidly in the past decade and innovative ‘biosmart’ theranostic materials are being synthesized and studied to combat the fast growth of cancer metastases. While current state-of-the-art oncology…
View article: Fluoroscopic 3D Image Generation from Patient-Specific PCA Motion Models Derived from 4D-CBCT Patient Datasets: A Feasibility Study
Fluoroscopic 3D Image Generation from Patient-Specific PCA Motion Models Derived from 4D-CBCT Patient Datasets: A Feasibility Study Open
A method for generating fluoroscopic (time-varying) volumetric images using patient-specific motion models derived from four-dimensional cone-beam CT (4D-CBCT) images was developed. 4D-CBCT images acquired immediately prior to treatment ha…
View article: An IoT System Using Deep Learning to Classify Camera Trap Images on the Edge
An IoT System Using Deep Learning to Classify Camera Trap Images on the Edge Open
Camera traps deployed in remote locations provide an effective method for ecologists to monitor and study wildlife in a non-invasive way. However, current camera traps suffer from two problems. First, the images are manually classified and…
View article: Fluoroscopic 3D Image Generation from Patient-Specific PCA Motion Models Derived from 4D-CBCT Patient Datasets: A Feasibility Study
Fluoroscopic 3D Image Generation from Patient-Specific PCA Motion Models Derived from 4D-CBCT Patient Datasets: A Feasibility Study Open
A method for generating fluoroscopic (time-varying) volumetric images using patient-specific motion models derived from 4-dimensional cone-beam CT (4D-CBCT) images is developed. 4D-CBCT images acquired immediately prior to treatment have t…
View article: Prediction of EV Charging Behavior Using Machine Learning
Prediction of EV Charging Behavior Using Machine Learning Open
As a key pillar of smart transportation in smart city applications, electric vehicles (EVs) are becoming increasingly popular for their contribution in reducing greenhouse gas emissions. One of the key challenges, however, is the strain on…
View article: Bioluminescence Imaging Applications in Cancer: A Comprehensive Review
Bioluminescence Imaging Applications in Cancer: A Comprehensive Review Open
Bioluminescence imaging (BLI), an optical preclinical imaging modality, is an invaluable imaging modality due to its low-cost, high throughput, fast acquisition times, and functional imaging capabilities. BLI is being extensively used in t…
View article: Quantifying day-to-day variations in 4DCBCT-based PCA motion models
Quantifying day-to-day variations in 4DCBCT-based PCA motion models Open
The aim of this paper is to quantify the day-to-day variations of motion models derived from pre-treatment 4-dimensional cone beam CT (4DCBCT) fractions for lung cancer stereotactic body radiotherapy (SBRT) patients. Motion models are buil…
View article: Machine Learning Approaches for EV Charging Behavior: A Review
Machine Learning Approaches for EV Charging Behavior: A Review Open
As the smart city applications are moving from conceptual models to development phase, smart transportation is one of smart cities applications and it is gaining ground nowadays. Electric Vehicles (EVs) are considered one of the major pill…
View article: Interfraction Variability of Motion Models Derived Using Patient 4-Dimensional Cone Beam Computed Tomography Images for Lung Cancer Stereotactic Body Radiation Therapy (SBRT) Patients
Interfraction Variability of Motion Models Derived Using Patient 4-Dimensional Cone Beam Computed Tomography Images for Lung Cancer Stereotactic Body Radiation Therapy (SBRT) Patients Open
View article: 3D delivered dose assessment using a 4DCT-based motion model
3D delivered dose assessment using a 4DCT-based motion model Open
With the availability of kV or MV projection images, the proposed approach is able to assess delivered doses for all respiratory phases during treatment. Compared to the planning dose based on 4DCT, the dose estimation using reconstructed …
View article: 3D fluoroscopic image estimation using patient-specific 4DCBCT-based motion models
3D fluoroscopic image estimation using patient-specific 4DCBCT-based motion models Open
3D fluoroscopic images represent volumetric patient anatomy during treatment with high spatial and temporal resolution. 3D fluoroscopic images estimated using motion models built using 4DCT images, taken days or weeks prior to treatment, d…