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PUBLICATIONS

 

1. Overview of Cancer Management - The role of medical imaging and machine learning techniques in early detection of cancer: Prospects, challenges, and future directions

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Suleiman, T.A., Tolulope, A.M., Wuraola, F.O., Olorunfemi, R., Kasali, W.A., Okorocha, B.O., Dirisu, C. and Njoku, P.C. (2023) Overview of Cancer Management - The role of medical imaging and machine learning techniques in early detection of cancer: Prospects, challenges, and future directions. Open Access Library Journal,10, 1-21. https://doi.org/10.4236/oalib.1110014

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  • Globally, the advent of new cases of cancer has been steadily increasing, with rising mortality and a significant impact on the economy. Most malignancy outcomes are linked to early detection, prompt diagnosis, and treatment. The need for early detection is crucial to cancer management. With these increasing numbers, there is a need for the adoption of emerging technologies such as machine learning to help improve the outcome of cancer management. For these reasons, in this paper, we reviewed the role of medical imaging and machine learning techniques in the management of cancer. In general, the technology used in imaging generates enormous data and hence, these data can be analysed using machine learning techniques and the output can be used to predict potential tumour cells resulting in a significant difference in the management of cancer. However, despite these advantages, there are some challenges in using machine learning which has also been discussed in this review, as well as some recommendations and future directions for the successful utilization of machine learning techniques in cancer management.

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2. Design and Development of a Hybrid Eye and Mobile Controlled Wheelchair Prototype using Haar cascade Classifier: A Proof of Concept

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Y. K. Ahmed, N. A. Danmusa, T. A. Suleiman, K. A. Salahudeen, S. Saminu, A. R. Zubair, A. B. Adelodun (2023) Design and Development of a Hybrid Eye and Mobile Controlled Wheelchair Prototype using Haar cascade Classifier: A Proof of Concept. Lecture Notes on Data Engineering and Communications Technologies, vol 181. Springer. https://doi.org/10.1007/978-3-031-36118-0_66

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  • According to the wheelchair foundation, about 1.86% of the world's population require a functional wheelchair. Most of these wheelchairs have manual control system which puts millions of people with total paralyzes (total loss of muscle control including the head) at a disadvantage. However, the majority of those who suffer from muscular and neurological disorders still retain the ability to move their eyes. Hence the concept of eye-controlled wheelchair. This paper focused on the design and development of a hybrid control system (eye and mobile interface) for a wheelchair prototype as a proof of concept. The system consists of eye image frames as input using Haar cascade classifier as the eye gaze direction detection algorithm with Open CV. It consists of a motor chassis that takes the place of a wheelchair, a raspberry pi4 model which acts as a mini-computer for image and information processing, and a laser sensor to achieve obstacle avoidance. The Bluetooth module enables serial communication between the motor chassis and the raspberry pi, while the power supply feeds the raspberry pi and the camera. The system performance evaluation was carried out using obstacle avoidance and navigation tests. An accuracy of 100% and 89% were achieved for obstacle avoidance and navigation, respectively, which shows that the system would be helpful for wheelchair users facing autonomous mobility issues.

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3. Telemedicine and Smart healthcare - The Role of Artificial Intelligence, 5G, Cloud Services, and Other Enabling Technologies 

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Suleiman, T.A. and Adinoyi, A. (2023) Telemedicine and Smart healthcare - The Role of Artificial Intelligence, 5G, Cloud Services, and Other Enabling Technologies. Int. J. Communications, Network and System Sciences, 16, 31-51. https://doi.org/10.4236/ijcns.2023.163003

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  • This paper discusses telemedicine and the employment of advanced mobile technologies in smart healthcare delivery. It covers the technological advances in connected smart healthcare, including the roles of artificial intelligence, machine learning, 5G and IoT platforms, and other enabling technologies. It also presents the challenges and potential risks that could arise from delivering connected smart healthcare services. Healthcare delivery is witnessing revolutions engineered by the developments in mobile connectivity and the plethora of platforms, applications, sensors, devices, and equipment that go along with it. Human society is evolving fast in response to these technological developments, which are also pushing the connectivity-providing sector to create and adopt new waves of network technologies. Consequently, new communications technologies have been introduced into the healthcare system and many novel applications have been developed to make it easier for sharing data in various forms and volumes within health-related services. These applications have also made it possible for telemedicine to be effectively adopted. This paper provides an overview of some of the recent developments within the space of mobile connectivity and telemedicine. 

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4. Inexpensive collapsible vibration plate for whole-body exercise and physiotherapy in low resource settings

(Manuscript being prepared for publication)

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  • Impairment of muscle strength and power of the lower extremities, balance/postural control, and walking ability are some of the common health issues in our community and to solve these problems most developed countries have vibrator plates due to their extreme importance in body stability, circulation, obesity control among others. In developing countries, vibrator exercising plates are quite expensive to purchase for low-salary earners and fitness centres, despite their need for them. This study presents the design, development and performance evaluation of a cost-effective vibration machine with a unique collapsible handle for easy mobility.

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PROJECTS

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1. Atlas-Based Brain MRI Tissue Segmentation

  • Segmentation using Atlas

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2. Brain Tissue Segmentation using Expectation Maximization

  • EM Algorithm built from scratch

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3. Deep Learning-Based Skin Lesion Classification

  • Implemented a novel two-step hierarchical binary classification with principal component analysis (PCA), cross-validation (CV), ML, deep learning, and transfer learning.

  • Built robust ML classifiers: Random Forest, Support Vector Machine (SVM), K-Nearest Neighbors (KNN), and Logistic Regression (LogReg) for the ML pipeline.

  • Adopted the feature extraction capabilities of pre-trained models (VGG16, RESNET, DENSENET) with ML models to enhance the accuracy of the classification model.

  • Built a CNN model with comparable accuracy to the pre-trained models.

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4. Classification of Alzheimer’s Disease using MRIs and Gene Expression data

  • Performed Min-Max Normalization to rescale the data values to a range between 0 and 1.

  • Performed PCA to reduce the curse of dimensionality and trained the data using LogReg.

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5. Hard Exudate Segmentation (Hex)

  • Preprocessed the images using Median Filtering and CLAHE

  • Carried out grayscale morphological operations using Top-hat, and Bottom-hat approaches and then performed global thresholding to the result.

  • Performed feature extraction from the images using Gray-Level Co-occurrence Matrix (GLCM), Gabor filters, Intensity-based features, and Shape descriptors.

  • Performed PCA to reduce the dimension of the extracted features and trained the model using SVM with regularization parameter and gamma to handle huge class imbalance.

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6. Additional Projects (Miscellaneous)

  • Intensity-Based Brain MRI Registration using Affine Transformation.

  • Breast Tumor Classification using KNN and Feature Engineering

  • Medical Service Provider System

  • Optical Disc Segmentation 

  • Breast Cancer Classification using LogReg and Decision Tree classifier

  • Several Image Processing practices using OpenCV - GitHub

 

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E- CONFERENCE AND WORKSHOP ATTENDED:

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1. Machine Learning Summer School on Applications in Science, Kraków, Poland, 2023

Some of the research also discussed includes but is not limited to:

  • Machine Learning in medical image analysis - challenges and opportunities

  • Bayesian models, and neural networks with applications in computational biology

  • Nothing Makes Sense in Deep Learning Except in the Light of the Simplicity Bias

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2. The 6th International Conference on Computer Science, Engineering and Education Applications (ICCSEEA2023), March 17 - 19, 2023, Warsaw, Poland

We presented our research on: 'Design and Development of a Hybrid Eye and Mobile Controlled Wheelchair Prototype using Haar cascade Classifier: A Proof of Concept'

Some of the research also discussed includes but is not limited to:

  • “Design of a Dynamic Probability-based Automatic Test Paper Generation System” - Presented by Fang Huang, Nanning University, China

  • “ Interest Point Detection at Digital Image Based on Averaging of Function” - Presented by Iryna Yurchuk, Teras Shevchenko National University of Kyiv, Ukraine

  • “Identifying the Application of Process Mining Technique to Visualise and Manage in the Healthcare Systems” Presented by Farhad Lotfi, University of Belgrade, Serbia

  • “A System of Stress Determination Based on Biomedical Indicators” Presented by Vitalii Savchyn, Lviv Polytechnic National University, Ukraine

 

3. 7th NANO Boston Conference (NWC Boston-2021), October 18-20 2021

Some of the research discussed includes but is not limited to:

  • “Orally Targeted Delivering Drugs to Diseases.” By Xing Zhou, Chongqing University of Technology, China

  • “Engineering of Nanomaterials for Drug Delivery and Bio-Sensing.” By Beatrice Fortuni, KU Leuven, Belgium

  • “Nanomedicine and Brain Diseases.” By Giovanni Tosi, University of Modena and Reggio Emilia, Italy

  • “Nano-pharmaceuticals: A Transformative Way for Cancer Treatments.” By Murali M. Yallapu, University of Texas Rio Grande Valley (UTRGV), TX, USA

4. Spotlight on Research at University of Southern California (USC), Viterbi School of Engineering 2021

The spotlight focuses on three researchers and their current research. These are:

  • “People-Centric AI and Sensing for Intelligent Built Environments.” By Professor Burcin Becerik-Gerber, Sept. 27th, 2021.

  • “Stem Technical Debt in Software Systems by Mining Architectural Information.” By Professor Nenad Medvidovic, Sept. 22nd, 2021.

  • “Mitigating Multi-Round Privacy Leakage in Federated Learning.” By Professor Salman Avestimehr, Sept. 15th, 2021.

 

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