Unsupervised Deep Anomaly Detection for Medical Images Using an Improved Adversarial Autoencoder

Author(s):  
Haibo Zhang ◽  
Wenping Guo ◽  
Shiqing Zhang ◽  
Hongsheng Lu ◽  
Xiaoming Zhao
Author(s):  
Thésése F. Eder ◽  
Katharina Scheiter ◽  
Juliane Richter ◽  
Constanze Keutel ◽  
Fabian Hüttig

Author(s):  
Qi Wei ◽  
Bibo Shi ◽  
Joseph Y. Lo ◽  
Lawrence Carin ◽  
Yinhao Ren ◽  
...  

2021 ◽  
pp. 128-140
Author(s):  
Yu Tian ◽  
Guansong Pang ◽  
Fengbei Liu ◽  
Yuanhong Chen ◽  
Seon Ho Shin ◽  
...  

Author(s):  
Kang Zhou ◽  
Jing Li ◽  
Weixin Luo ◽  
Zhengxin Li ◽  
Jianlong Yang ◽  
...  

2018 ◽  
Vol 18 (1) ◽  
pp. 20-32 ◽  
Author(s):  
Jong-Min Kim ◽  
Jaiwook Baik

EMJ Radiology ◽  
2020 ◽  
Author(s):  
Filippo Pesapane

Radiomics is a science that investigates a large number of features from medical images using data-characterisation algorithms, with the aim to analyse disease characteristics that are indistinguishable to the naked eye. Radiogenomics attempts to establish and examine the relationship between tumour genomic characteristics and their radiologic appearance. Although there is certainly a lot to learn from these relationships, one could ask the question: what is the practical significance of radiogenomic discoveries? This increasing interest in such applications inevitably raises numerous legal and ethical questions. In an environment such as the technology field, which changes quickly and unpredictably, regulations need to be timely in order to be relevant.  In this paper, issues that must be solved to make the future applications of this innovative technology safe and useful are analysed.


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