Year: 2025
Type: book-chapter
Abstract: The automatic detection of white blood cancer is carried out by examining bone marrow microscopic images, which is an important development in the medical profession.For the purpose of accurately recognizing and categorizing leukemic cells, we suggest a method for using convolutional neural networks.Using the CBC dataset, the proposed study offers a reliable method for detecting the white blood cancer.The model first pre-processes the photos and extracts the best characteristics after being trained on cell images.For the purpose of accurately recognizing and categorizing leukemic cells, we suggest a method for using convolutional neural networks.Our approach makes use of CNNs' strong extraction capabilities, which is why our system proved to be highly successful in differentiating between healthy and cancerous cells in bone marrow samples.A large, extensive dataset of labelled microscopic pictures will be used to train and validate the suggested system.
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4415763563