Uncertainty Estimation for Dual View X-ray Mammographic Image Registration Using Deep Ensembles
William C. Walton,
Seung-Jun Kim
Abstract:Techniques are developed for generating uncertainty estimates for convolutional neural network (CNN)-based methods for registering the locations of lesions between the craniocaudal (CC) and mediolateral oblique (MLO) mammographic X-ray image views. Multi-view lesion correspondence is an important task that clinicians perform for characterizing lesions during routine mammographic exams. Automated registration tools can aid in this task, yet if the tools also provide confidence estimates, they can be of greater … Show more
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