Automated segmentation of dermal fillers in OCT images of mice using convolutional neural networks
نویسندگان
چکیده
منابع مشابه
Topology guaranteed segmentation of the human retina from OCT using convolutional neural networks
Optical coherence tomography (OCT) is a noninvasive imaging modality which can be used to obtain depth images of the retina. The changing layer thicknesses can thus be quantified by analyzing these OCT images, moreover these changes have been shown to correlate with disease progression in multiple sclerosis. Recent automated retinal layer segmentation tools use machine learning methods to perfo...
متن کاملAutomated OCT Segmentation for Images with DME
Diabetic macular edema (DME) is a leading cause of vision loss in patients with diabetes. The World Health Organization estimates that by the year 2020, there will be 75 million blind people and 314 million partially blind people in the world [1]. While treatments are available, including intra-vitreal injections and macular laser therapy, not all patients respond to these. Currently, there are...
متن کاملFine Hand Segmentation using Convolutional Neural Networks
We propose a method for extracting very accurate masks of hands in egocentric views. Our method is based on a novel Deep Learning architecture: In contrast with current Deep Learning methods, we do not use upscaling layers applied to a low-dimensional representation of the input image. Instead, we extract features with convolutional layers and map them directly to a segmentation mask with a ful...
متن کاملA New Method to Improve Automated Classification of Heart Sound Signals: Filter Bank Learning in Convolutional Neural Networks
Introduction: Recent studies have acknowledged the potential of convolutional neural networks (CNNs) in distinguishing healthy and morbid samples by using heart sound analyses. Unfortunately the performance of CNNs is highly dependent on the filtering procedure which is applied to signal in their convolutional layer. The present study aimed to address this problem by a...
متن کاملSegmentation of Drosophila Heart in Optical Coherence Microscopy Images Using Convolutional Neural Networks
Convolutional neural networks are powerful tools for image segmentation and classification. Here, we use this method to identify and mark the heart region of Drosophila at different developmental stages in the cross-sectional images acquired by a custom optical coherence microscopy (OCM) system. With our well-trained convolutional neural network model, the heart regions through multiple heartbe...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Biomedical Optics Express
سال: 2019
ISSN: 2156-7085,2156-7085
DOI: 10.1364/boe.10.001315