تقرير
YNetr: Dual-Encoder architecture on Plain Scan Liver Tumors (PSLT)
| العنوان: | YNetr: Dual-Encoder architecture on Plain Scan Liver Tumors (PSLT) |
|---|---|
| المؤلفون: | Sheng, Wen, Zheng, Zhong, Liu, Jiajun, Lu, Han, Zhang, Hanyuan, Jiang, Zhengyong, Zhang, Zhihong, Zhu, Daoping |
| سنة النشر: | 2024 |
| المجموعة: | Computer Science |
| مصطلحات موضوعية: | Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning |
| الوصف: | Background: Liver tumors are abnormal growths in the liver that can be either benign or malignant, with liver cancer being a significant health concern worldwide. However, there is no dataset for plain scan segmentation of liver tumors, nor any related algorithms. To fill this gap, we propose Plain Scan Liver Tumors(PSLT) and YNetr. Methods: A collection of 40 liver tumor plain scan segmentation datasets was assembled and annotated. Concurrently, we utilized Dice coefficient as the metric for assessing the segmentation outcomes produced by YNetr, having advantage of capturing different frequency information. Results: The YNetr model achieved a Dice coefficient of 62.63% on the PSLT dataset, surpassing the other publicly available model by an accuracy margin of 1.22%. Comparative evaluations were conducted against a range of models including UNet 3+, XNet, UNetr, Swin UNetr, Trans-BTS, COTr, nnUNetv2 (2D), nnUNetv2 (3D fullres), MedNext (2D) and MedNext(3D fullres). Conclusions: We not only proposed a dataset named PSLT(Plain Scan Liver Tumors), but also explored a structure called YNetr that utilizes wavelet transform to extract different frequency information, which having the SOTA in PSLT by experiments. Comment: My academic research interests have undergone significant changes. I believe that continuing to retain the paper is no longer in line with my academic development path, and may also mislead readers. And some of the content may involve the boundaries of personal privacy. To respect and protect the privacy of relevant personnel, I decided to withdraw it to avoid any unnecessary controversy or harm |
| نوع الوثيقة: | Working Paper |
| URL الوصول: | http://arxiv.org/abs/2404.00327 |
| رقم الأكسشن: | edsarx.2404.00327 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |