Improving the accuracy of diabetic retinopathy severity classification with transfer learning

NB Thota, DU Reddy - 2020 IEEE 63rd International Midwest …, 2020 - ieeexplore.ieee.org
Diabetic Retinopathy (DR) is a major cause of blindness in Diabetic patients, and its early
detection benefits diagnosis and subsequent treatment methods. In this work, a …

Multi-target deep learning for algal detection and classification

P Qian, Z Zhao, H Liu, Y Wang, Y Peng… - 2020 42nd annual …, 2020 - ieeexplore.ieee.org
Water quality has a direct impact on industry, agriculture, and public health. Algae species
are common indicators of water quality. It is because algal communities are sensitive to …

Sea-net: Squeeze-and-excitation attention net for diabetic retinopathy grading

Z Zhao, K Chopra, Z Zeng, X Li - 2020 IEEE International …, 2020 - ieeexplore.ieee.org
Diabetes is one of the most common disease in individuals. Diabetic retinopathy (DR) is a
complication of diabetes, which could lead to blindness. Automatic DR grading based on …

Automatic diabetic retinopathy grading via self-knowledge distillation

L Luo, D Xue, X Feng - Electronics, 2020 - mdpi.com
Diabetic retinopathy (DR) is a common fundus disease that leads to irreversible blindness,
which plagues the working-age population. Automatic medical imaging diagnosis provides a …

Cost-sensitive regularization for diabetic retinopathy grading from eye fundus images

A Galdran, J Dolz, H Chakor, H Lombaert… - … Image Computing and …, 2020 - Springer
Assessing the degree of disease severity in biomedical images is a task similar to standard
classification but constrained by an underlying structure in the label space. Such a structure …

Automatic measurement of fetal cavum septum pellucidum from ultrasound images using deep attention network

Y Wu, K Shen, Z Chen, J Wu - 2020 IEEE International …, 2020 - ieeexplore.ieee.org
The measurement of cavum septum pellucidum is an important step in prenatal testing.
However, this process is usually done manually, which is such a difficult and time …

Deep learning and its application in diabetic retinopathy screening

B Zou, X Shan, C Zhu, Y Dai, K Yue… - Chinese Journal of …, 2020 - Wiley Online Library
Deep learning (DL), especially Convolutional neural networks (CNN), has gained wide
popularity in various image processing tasks. With the significant achievements obtained in …

Multi-phase cross-modal learning for noninvasive gene mutation prediction in hepatocellular carcinoma

J Gu, Z Zhao, Z Zeng, Y Wang, Z Qiu… - 2020 42nd annual …, 2020 - ieeexplore.ieee.org
Hepatocellular carcinoma (HCC) is the most common type of primary liver cancer and the
fourth most common cause of cancer-related death worldwide. Understanding the …

Multi-instance multi-label learning for gene mutation prediction in hepatocellular carcinoma

K Xu, Z Zhao, J Gu, Z Zeng, CW Ying… - 2020 42nd annual …, 2020 - ieeexplore.ieee.org
Gene mutation prediction in hepatocellular carcinoma (HCC) is of great diagnostic and
prognostic value for personalized treatments and precision medicine. In this paper, we …

Deeply supervised active learning for finger bones segmentation

Z Zhao, X Yang, B Veeravalli… - 2020 42nd Annual …, 2020 - ieeexplore.ieee.org
Segmentation is a prerequisite yet challenging task for medical image analysis. In this
paper, we introduce a novel deeply supervised active learning approach for finger bones …