Artificial intelligence (AI) using deep-learning (DL) has emerged as a breakthrough computer technology. By the era of big data, the accumulation of an enormous number of digital images and medical records drove the need for the utilization of AI to ...
Diagnosis in dermatology is largely based on contextual factors going far beyond the visual and dermoscopic inspection of a lesion. Diagnostic tools such as the different types of dermoscopy, confocal microscopy and optical coherence tomography (OCT)...
The study of neuronal morphology in relation to function, and the development of effective medicines to positively impact this relationship in patients suffering from neurodegenerative diseases, increasingly involves image-based high-content screenin...
Mathematical biosciences and engineering : MBE
Mar 8, 2019
Automatically identifying semantic concepts from medical images provides multimodal insights for clinical research. To study the effectiveness of concept detection on large scale medical images, we reconstructed over 230,000 medical image-concepts pa...
Annals of clinical and laboratory science
Mar 1, 2019
Recent studies have shown promising results in using Deep Learning to detect malignancy in whole slide imaging, however, they were limited to just predicting a positive or negative finding for a specific neoplasm. We attempted to use Deep Learning wi...
We propose a deep learning-based restoration method to remove honeycomb patterns and improve resolution for fiber bundle (FB) images. By building and calibrating a dual-sensor imaging system, we capture FB images and corresponding ground truth data t...
Mathematical biosciences and engineering : MBE
Feb 20, 2019
Deep learning tools have been a new way for privacy attacks on remote sensing images. However, since labeled data of privacy objects in remote sensing images are less, the samples for training are commonly small. Besides, traditional deep neural netw...
Mathematical biosciences and engineering : MBE
Feb 19, 2019
The Hough transform has been widely used in image analysis and digital image processing due to its capability of transforming image space detection to parameter space accumulation. In this paper, we propose a novel Angle-Aided Circle Detection (AACD)...
In breast cancer, 20%-30% of cases require a second surgery because of incomplete excision of malignant tissues. Therefore, to avoid the risk of recurrence, accurate detection of the cancer margin by the clinician or surgeons needs some assistance. I...
In a wide range of semantic segmentation tasks, fully convolutional neural networks (F-CNNs) have been successfully leveraged to achieve the state-of-the-art performance. Architectural innovations of F-CNNs have mainly been on improving spatial encod...
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