scholarly journals STUDY ON IMAGE DIAGNOSIS OF TIMBER HOUSES DAMAGED BY EARTHQUAKE USING DEEP LEARNING

2020 ◽  
Vol 85 (770) ◽  
pp. 529-538
Author(s):  
Hiroyuki CHIDA ◽  
Noriyuki TAKAHASHI
Keyword(s):  
Deep Learning ◽  
Image Diagnosis

scholarly journals The Utility of Applying Various Image Preprocessing Strategies to Reduce the Ambiguity in Deep Learning-based Clinical Image Diagnosis

2020 ◽  
Vol 19 (2) ◽  
pp. 92-98
Author(s):  
Yasuhiko Tachibana ◽  
Takayuki Obata ◽  
Jeff Kershaw ◽  
Hironao Sakaki ◽  
Takuya Urushihata ◽  
...  
Keyword(s):  
Deep Learning ◽  
Clinical Image ◽  
Image Preprocessing ◽  
Image Diagnosis

Deep learning-based cardiovascular image diagnosis: A promising challenge

2020 ◽  
Vol 110 ◽  
pp. 802-811 ◽  
Author(s):  
Kelvin K.L. Wong ◽  
Giancarlo Fortino ◽  
Derek Abbott
Keyword(s):  
Deep Learning ◽  
Cardiovascular Image ◽  
Image Diagnosis

scholarly journals Efficient Deep-Learning-Based Autoencoder Denoising Approach for Medical Image Diagnosis

2022 ◽  
Vol 70 (3) ◽  
pp. 6107-6125
Author(s):  
Walid El-Shafai ◽  
Samy Abd El-Nabi ◽  
El-Sayed M. El-Rabaie ◽  
Anas M. Ali ◽  
Naglaa F. Soliman ◽  
...  
Keyword(s):  
Deep Learning ◽  
Medical Image ◽  
Medical Image Diagnosis ◽  
Image Diagnosis

scholarly journals Pathological Evidence Exploration in Deep Retinal Image Diagnosis

2019 ◽  
Vol 33 ◽  
pp. 1093-1101 ◽  
Author(s):  
Yuhao Niu ◽  
Lin Gu ◽  
Feng Lu ◽  
Feifan Lv ◽  
Zongji Wang ◽  
...  
Keyword(s):  
Diabetic Retinopathy ◽  
Deep Learning ◽  
Medical Research ◽  
Retinal Image ◽  
Medical Diagnosis ◽  
Vessel Segmentation ◽  
Panel Survey ◽  
Successful Performance ◽  
Koch’S Postulates ◽  
Image Diagnosis

Though deep learning has shown successful performance in classifying the label and severity stage of certain disease, most of them give few evidence on how to make prediction. Here, we propose to exploit the interpretability of deep learning application in medical diagnosis. Inspired by Koch’s Postulates, a well-known strategy in medical research to identify the property of pathogen, we define a pathological descriptor that can be extracted from the activated neurons of a diabetic retinopathy detector. To visualize the symptom and feature encoded in this descriptor, we propose a GAN based method to synthesize pathological retinal image given the descriptor and a binary vessel segmentation. Besides, with this descriptor, we can arbitrarily manipulate the position and quantity of lesions. As verified by a panel of 5 licensed ophthalmologists, our synthesized images carry the symptoms that are directly related to diabetic retinopathy diagnosis. The panel survey also shows that our generated images is both qualitatively and quantitatively superior to existing methods.

Sign in / Sign up

Export Citation Format

Share Document