In this work, we propose to use a 3D deep attention U-Net method to segment the thyroid from CT image automatically. ... The resultant DSC, precision, and recall ...
In this work, we propose to use a 3D deep attention U-Net method to segment the thyroid from CT image automatically. The quantitative evaluation of the ...
To overcome issues of using small datasets, various data augmentation techniques have been developed. In this paper, an approach for the whole heart ...
Mar 22, 2023 · Here, we aimed to develop a deep-learning-based CT-free quantitative thyroid SPECT that can generate an attenuation map (μ-map) and ...
In this study, a progressive learning vector quantization neural network (PLVQNN) combined with a preprocessing procedure is proposed for automatic thyroid ...
Segmenting accurate thyroid nodules in medical ultrasound images is always non-trivial due to the large variation in size, shape and texture of nodules, ...
Missing: CT | Show results with:CT
Apr 14, 2023 · Webb et al. [50] proposed DeepLabv3+ based convolutional LSTM to segment both nodules and glands. The method obtained 53.3% nodule IoU and 73.9% ...
Feb 28, 2024 · An innovative method for classifying thyroid cancer based on multimodal domain adaptation was presented by Zhao et al. The researchers developed ...
SkaNet highlights the potential of combining thyroid nodule segmentation and diagnosis with knowledge augmented learning into a unified framework, which ...
The purpose of this study is to develop a deep learning method for thyroid delineation with high accuracy, efficiency, and robustness in noncontrast-enhanced ...