Artificial convolutional neural network in object detection and semantic segmentation for medical imaging analysis

R Yang, Y Yu - Frontiers in oncology, 2021 - frontiersin.org
In the era of digital medicine, a vast number of medical images are produced every day.
There is a great demand for intelligent equipment for adjuvant diagnosis to assist medical …

Artificial intelligence and deep learning in ophthalmology

DSW Ting, LR Pasquale, L Peng… - British Journal of …, 2019 - bjo.bmj.com
Artificial intelligence (AI) based on deep learning (DL) has sparked tremendous global
interest in recent years. DL has been widely adopted in image recognition, speech …

CPFNet: Context pyramid fusion network for medical image segmentation

S Feng, H Zhao, F Shi, X Cheng… - IEEE transactions on …, 2020 - ieeexplore.ieee.org
Accurate and automatic segmentation of medical images is a crucial step for clinical
diagnosis and analysis. The convolutional neural network (CNN) approaches based on the …

[HTML][HTML] Artificial intelligence in retina

U Schmidt-Erfurth, A Sadeghipour, BS Gerendas… - Progress in retinal and …, 2018 - Elsevier
Major advances in diagnostic technologies are offering unprecedented insight into the
condition of the retina and beyond ocular disease. Digital images providing millions of …

[HTML][HTML] Trustworthy AI: closing the gap between development and integration of AI systems in ophthalmic practice

C González-Gonzalo, EF Thee, CCW Klaver… - Progress in retinal and …, 2022 - Elsevier
An increasing number of artificial intelligence (AI) systems are being proposed in
ophthalmology, motivated by the variety and amount of clinical and imaging data, as well as …

RETOUCH: The retinal OCT fluid detection and segmentation benchmark and challenge

H Bogunović, F Venhuizen, S Klimscha… - IEEE transactions on …, 2019 - ieeexplore.ieee.org
Retinal swelling due to the accumulation of fluid is associated with the most vision-
threatening retinal diseases. Optical coherence tomography (OCT) is the current standard of …

Deep learning based joint segmentation and characterization of multi-class retinal fluid lesions on OCT scans for clinical use in anti-VEGF therapy

B Hassan, S Qin, R Ahmed, T Hassan… - Computers in Biology …, 2021 - Elsevier
Background In anti-vascular endothelial growth factor (anti-VEGF) therapy, an accurate
estimation of multi-class retinal fluid (MRF) is required for the activity prescription and …

Application of machine learning in ophthalmic imaging modalities

Y Tong, W Lu, Y Yu, Y Shen - Eye and Vision, 2020 - Springer
In clinical ophthalmology, a variety of image-related diagnostic techniques have begun to
offer unprecedented insights into eye diseases based on morphological datasets with …

Deep-learning based multiclass retinal fluid segmentation and detection in optical coherence tomography images using a fully convolutional neural network

D Lu, M Heisler, S Lee, GW Ding, E Navajas… - Medical image …, 2019 - Elsevier
As a non-invasive imaging modality, optical coherence tomography (OCT) can provide
micrometer-resolution 3D images of retinal structures. These images can help reveal …

[HTML][HTML] AI-based monitoring of retinal fluid in disease activity and under therapy

U Schmidt-Erfurth, GS Reiter, S Riedl… - Progress in retinal and …, 2022 - Elsevier
Retinal fluid as the major biomarker in exudative macular disease is accurately visualized by
high-resolution three-dimensional optical coherence tomography (OCT), which is used …