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Change detection of pulmonary embolism using isomeric cluster and computer vision
2022
IAES International Journal of Artificial Intelligence (IJ-AI)
<p>Visual change detection functions in X-ray analytics and computer vision attempt to divide X-ray images toward front and backside areas. There are various difficulties in change detection such as weather changes and shadows; real-time processing; intermittent object motion; lighting variation; and diverse object forms. Traditionally, this issue has been addressed via backdrop modeling methods and the creation of custom features. We present a new feature descriptor called pulmonary embolism
doi:10.11591/ijai.v11.i2.pp787-798
fatcat:vdbveabwqncixc26mskyhwhmsi