Blood Cancer Cell Detection Using YOLO with 3D Depth Imaging for Automated Hematological Diagnosis

Author(s)	Mr. Darshan M, Mr. Nayim A Dalawai, Mr. Prathamraj P B, Mr. Aditya C R
Country	India
Abstract	Early detection of blood cancers remains a critical challenge due to the limitations of conventional manual blood smear examinations, which are slow and dependent on expert interpretation. In response, this study presents an AI-driven approach that leverages the YOLO object detection framework paired with a standard webcam for real-time analysis of blood samples. Trained on a dataset of major blood cell types, the system demonstrates promising capability in distinguishing abnormal cells. By offering a cost-effective and accessible diagnostic aid, the method shows potential to support pathologists in the early screening of leukemia, lymphoma, myeloma, and related disorders.
Keywords	Blood Cancer Detection, YOLO Object Detection, 3D Depth Imaging, Automated Hematological Diagnosis, Deep Learning in Healthcare, Medical Image Analysis, Computer-Aided Diagnosis, Artificial Intelligence in Oncology
Field	Engineering
Published In	Volume 7, Issue 6, November-December 2025
Published On	2025-11-05
DOI	https://doi.org/10.36948/ijfmr.2025.v07i06.55418

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