Object detection based on deep learning has been widely studied in many fields such as transportation and military, and has achieved remarkable results. In order to further study its usability in medical image diagnosis, two classical models of object detection algorithms, SSD and Faster RCNN, are proposed to appliy to the lesion detection of lung cancer pathological images. The experimental comparison shows that the average processing time of Faster RCNN is about 4.6 times longer than that of SSD, but the recognition accuracy and precision are higher than that of SSD, and the model performance of Faster RCNN is much better. The research results show that the object detection algorithm can realize the intelligent diagnosis of lung cancer pathological images and improve the diagnosis rate of lung cancer.
WU Jianguo
,
YANG Xiaoru
,
WANG Pan
,
WU Junfang
,
LI Ruikai
. Application of object detection algorithm in pathology diagnosis of lung cancer[J]. Journal of Hebei University(Natural Science Edition), 2023
, 43(5)
: 546
-552
.
DOI: 10.3969/j.issn.1000-1565.2023.05.014
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