Medical Image Learning with Limited and Noisy Data

Explore the cutting-edge research in "Medical Image Learning with Limited and Noisy Data," authored by Ghada Zamzmi and published by Springer International Publishing AG in 2022. This comprehensive volume, spanning 240 pages, presents the proceedings from the First Workshop on Medical Image Learning with Limited and Noisy Data (MILLanD 2022), which took place alongside the prestigious MICCAI 2022 conference. Delve into innovative methodologies and findings that address the challenges of medical image analysis in the presence of limited and noisy datasets. This book is an essential resource for researchers and practitioners looking to enhance their understanding of medical imaging technologies and improve their applications in clinical settings. Perfect for anyone interested in the intersection of artificial intelligence and healthcare, this 2022 edition is a must-have addition to your professional library.