EchoVisuAL: Efficient Segmentation of Echocardiograms Using Deep Active Learning
Author:
Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-66958-3_27
Reference23 articles.
1. Akkus, Z., et al.: Artificial intelligence (AI)-empowered echocardiography interpretation: a state-of-the-art review. J. Clin. Med. 10(7), 1391 (2021)
2. Barry, T., et al.: The role of artificial intelligence in echocardiography. J. Imaging 9(2), 50 (2023)
3. Brandenburg, J.M., et al.: Active learning for extracting surgomic features in robot-assisted minimally invasive esophagectomy: a prospective annotation study. Surg. Endosc. 37(11), 8577–8593 (2023)
4. Bukas, C., et al.: Echo2pheno: a deep-learning application to uncover echocardiographic phenotypes in conscious mice. Mammalian Genome 34(2), 200–215 (2023)
5. Duan, C., et al.: Fully automated mouse echocardiography analysis using deep convolutional neural networks. Am. J. Physiol.-Heart Circul. Physiol. 323(4), H628–H639 (2022)
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