Enhancing Acute Lymphoblastic Leukemia Diagnosis Through Dual Deep Learning Approaches
Muhammad Shameem P, Jemsheer Ahmed P, Nisa Parvin K P, M T Safa, Sahana V P, Hima Musthafa T H · 2024
Leukemia, a life-threatening blood cancer, de-mands early and accurate diagnosis for effective treatment. This project aims to bring out the potential of dual deep learning techniques to enhance acute lymphoblastic leukemia detection. Our approach combines the capabilities of Convolutional Neural Networks (CNNs). We also propose a mobile application that integrates these dual deep learning models to provide a user-friendly and accessible solution for acute lymphoblastic leukemia detection. High-resolution medical images, such as peripheral blood smears undergo thorough examination using advanced CNN architectures. Sequential data, encompassing temporal information like cell morphology evolution, genetic markers, and patient histories, are systematically analyzed. The dual deep learning model is trained on an extensive and diverse leukemia dataset, encompassing various subtypes and disease stages. Fine-tuning and transfer learning techniques are employed to optimize model performance. Once trained, the system is assured to efficiently evaluate new patient data,providing rapid and highly accurate leukemia diagnosis. The app is trained by using a comprehensive dataset of annotated blood cell images. The app will be designed with a user-friendly interface, enabling medical professionals to easily upload and analyze blood samples. The system's output will provide rapid and accurate leukemia detection, reducing the time and subjectivity associated with manual diagnosis. In summary our project aims to advance acute lymphoblastic leukemia detection by combining two or more powerful deep learning methods to work together effectively. This system holds the promise of assisting healthcare practitioners in making more informed decisions, ultimately leading to improved patient outcomes and more effective management of this life-threatening disease