cats-and-dogs-classification:Oxford-IIIT-Pet数据集-使用CNN进行图像分类 行业研究 - 数据集漫游**宇宙 上传35.57 KB 文件格式 zip python pytorch convolutional-neural-networks oxford imgaug 猫狗分类 牛津-IIIT宠物数据集。 问题在于对数据集中显示的每种动物进行分类。 第一步是对猫和猫之间的品种进行分类,...
3D CNN Design for the Classification of Alzheimer's Disease Using Brain MRI and PET 来自 Semantic Scholar 喜欢 0 阅读量: 59 作者:B Khagi,GR Kwon 摘要: Attempt to diagnose Alzheimer's disease (AD) using imaging modalities is one of the scopes of deep learning. While considering the ...
Positron...doi:10.1007/978-981-13-8566-7_16Sato, RyosukeRitsumeikan UniversityIwamoto, YutaroRitsumeikan UniversityCho, KookDong-A UniversityKang, Do-YoungDong-A UniversityChen, Yen-WeiRitsumeikan University
Tissue classification as a potential approach for attenuation correction in whole-body PET/MRI: evaluation with PET/CT data. J Nucl Med. 2009;50(4):520–6. Article Google Scholar Hofmann M, Bezrukov I, Mantlik F, Aschoff P, Steinke F, Beyer T, et al. MRI-based attenuation correction...
For suspicious lesions not confirmed by histopathology, other imaging modalities (US, MRI, CT), biochemistry, and medical records will be used for classification. The clinical impact of [68Ga]Ga-FAPI-46 PET/CT, both at primary staging and post-NACT staging, will be evaluated at a ...
在这项研究中,使用108个手动分割的基于PSMA的PET/CT扫描的数据集来训练不同的CNNs进行自动肾脏分割。应用了不同的方法来利用自动分割过程中的PET信息。最后,由一位经验丰富的核医学医师对100名额外患者的自动分割(包括和不包括PET信息)进行了视觉评估。
We propose a fully automatic multi-task Bayesian model, named Bayesian Sequential Network (BSN), for predicting high-grade (Gleason[Math Processing Error]≥8) prostate cancer (PCa) prognosis using pre-prostatectomy FDG-PET/CT images and clinical data. BSN performs one classification task and five...
Performance of the progression risk model was evaluated using AUC, accuracy, sensitivity, and specificity. Performance was additionally re-evaluated with the second manual segmentation. Heatmaps generated using the Grad-CAM algorithm with absolute gradients from the CT and PET CNN models with manual ...
Using data from the PROMISE repository, the constructed model was evaluated, and the results revealed improved recall. Researchers in Ref. [11] used data from seven prior iterations of the same programme to analyse several classification algorithms, such as NBs (Naive Bayes), DTs (Decision Trees...
在这项研究中,使用108个手动分割的基于PSMA的PET/CT扫描的数据集来训练不同的CNNs进行自动肾脏分割。应用了不同的方法来利用自动分割过程中的PET信息。最后,由一位经验丰富的核医学医师对100名额外患者的自动分割(包括和不包括PET信息)进行了视觉评估。