Exploring pretrained encoders for lung nodule segmentation task using LIDC-IDRI dataset
Author:
Funder
department of science & technology
Publisher
Springer Science and Business Media LLC
Subject
Computer Networks and Communications,Hardware and Architecture,Media Technology,Software
Link
https://link.springer.com/content/pdf/10.1007/s11042-023-15871-3.pdf
Reference44 articles.
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2. Ali Z, Irtaza A, Maqsood M (2022) An efficient U-net framework for lung nodule detection using densely connected dilated convolutions. J Supercomput 78(2):1602–1623
3. Banu SF, Sarker MMK, Abdel-Nasser M, Rashwan HA, Puig D (2021) Weu-net: a weight excitation U-net for lung nodule segmentation. In: CCIA, pp 349–356
4. Banu SF, Sarker M, Kamal M, Abdel-Nasser M, Puig D, Raswan HA (2021) Aweu-net: an attention-aware weight excitation U-net for lung nodule segmentation. Appl Sci 11(21):10132
5. Bianconi F, Fravolini ML, Pizzoli S, Palumbo I, Minestrini M, Rondini M, Nuvoli S, Spanu A, Palumbo B (2021) Comparative evaluation of conventional and deep learning methods for semi-automated segmentation of pulmonary nodules on CT. Quant Imaging Med Surg 11(7):3286
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