Artificial Intelligence–Based Methods for Integrating Local and Global Features for Brain Cancer Imaging: Scoping Review by Hazrat Ali (421019)

Multiclass ensemble framework for enhanced prostate gland Segmentation: Integrating Self-ONN decoders with EfficientNet by Md. Shaheenur Islam Sumon (22045907)

An Integrated Design for Classification and Localization of Diabetic Foot Ulcer Based on CNN and YOLOv2-DFU Models by Javaria Amin (14557730)

Dynamic model scaling based on segmented tumor size for breast cancer detection by Younes Akbari (16303286)

“…This study introduces an adaptive method that intelligently matches model complexity to tumor characteristics by integrating a Denoising Diffusion Probabilistic Model (DDPM), a generative model that iteratively improves segmentation accuracy by progressively removing noise, for tumor region segmentation with a range of EfficientNet architectures for classification. …”

Automated Detection of Colorectal Polyp Utilizing Deep Learning Methods With Explainable AI by Md. Faysal Ahamed (21842396)

“…Conclusively, integrating these advanced computer-aided methods substantially enhances colonoscopy procedures by mitigating the risks of colorectal cancer.…”

Deep learning-driven segmentation of ischemic stroke lesions using multi-channel MRI by Ashiqur Rahman (3969347)

“…Trained and evaluated on the ISLES 2022 dataset, the model achieved Dice Similarity Coefficients (DSC) of 83.88 % using <u>DWI </u>alone, 85.86 % with DWI and<u> ADC</u>, and 87.49 % with the integration of DWI, <u>ADC</u>, and eDWI. This approach not only outperforms existing methods but also addresses key limitations in current segmentation practices. …”

Deep learning for surgical instrument recognition and segmentation in robotic-assisted surgeries: a systematic review by Fatimaelzahraa Ali Ahmed (22224640)

“…This systematic review examines 48 studies that utilize advanced DL methods and architectures. These sophisticated DL models have shown notable improvements in the precision and efficiency of detecting and segmenting surgical tools. …”

Pool Free Rapid Segmentation Network (PFRS-Net) to detect human blastocyst compartments for embryonic assessment by Abida Hussain (22049752)

“…The experimental outcomes demonstrate superior segmentation performance in detecting blastocyst components, which is vital for embryonic research and analysis.…”

LSCS-Net: A lightweight skin cancer segmentation network with densely connected multi-rate atrous convolution by Sadia Din (18136919)

“…<p>The rising occurrence and notable public health consequences of skin cancer, especially of the most challenging form known as melanoma, have created an urgent demand for more advanced approaches to disease management. The integration of modern computer vision methods into clinical procedures offers the potential for enhancing the detection of skin cancer . …”

Hybrid Neural Networks for Precise Hydronephrosis Classification Using Deep Learning by Abdus Salam (1918387)

“…</p><h3 dir="ltr">Results</h3><p dir="ltr">The model achieved strong segmentation performance for kidneys (Dice: 0.92, precision: 0.93, recall: 0.91) and fluid regions (Dice: 0.89, precision: 0.90, recall: 0.88), outperforming baseline methods. …”

Integration of Textural and Material Information into BIM Using Spectrometry and Infrared Sensing by Zabin, Asem Ahmad

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Pavement Crack Assessment Using Satellite Remote Sensing and Deep Learning Model by Al Adab, Maryam

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A transfer function method for the continuous assessment of baroreflex control of renal sympathetic nerve activity in rats by Kanbar, Roy

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Exploring the potential of onboard energy scavenging subsystems for generating valuable data by Raziq Yaqub (16488878)

“…This gathered data is seamlessly synchronized with GPS coordinates and timestamps, meticulously organized within a system architecture, and harnessed through meticulously crafted Python code. The wealth of data that we obtain from an onboard energy scavenging subsystem holds significant potential. …”

Hybrid Classification Approach Utilizing DenseUNet+ for Diabetic Macular Edema Disorder Detection by Abualigah, Laith

“…Leveraging advancements in computer-assisted diagnostics, this study proposes a novel approach utilizing the DenseUNet+ architecture tailored for precise segmentation across diverse image modalities. The proposed method integrates data from four modalities within dense block structures, followed by linear operations and concatenation to enhance feature representation. …”
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Early diabetic retinopathy diagnosis based on local retinal blood vessel analysis in optical coherence tomography angiography (OCTA) images by Eladawi, Nabila

“…The high capability of our segmentation approach stems from using a joint Markov–Gibbs random field stochastic model integrating a 3D spatial statistical model with a first‐order appearance model of the blood vessels. …”
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Meta-Heuristic Algorithm-Tuned Neural Network for Breast Cancer Diagnosis Using Ultrasound Images by Ahila A (18394806)

“…Numerical analysis revealed that the proposed work can yield higher classification accuracy when compared to the prevailing methods and thereby proves its potential in effective breast tumor detection and classification. …”

Hand-Crafted Features with Simple Deep Learning Architectures for Human Activity Recognition by Albadawi, Yaman Sufian

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Transforming Dermatopathology With AI: Addressing Bias, Enhancing Interpretability, and Shaping Future Diagnostics by Diala Ra'Ed Kamal Kakish (22330627)

“…Inclusive frameworks, such as the Monk scale, and advanced segmentation methods effectively address dataset biases. …”

Applications of artificial intelligence in ultrasound imaging for carpal-tunnel syndrome diagnosis: a scoping review by Yosra Magdi Mekki (21673721)

“…</p><h3>Conclusion</h3><p dir="ltr">The integration of AI in US imaging for CTS diagnosis holds significant promise for transforming clinical practice. …”