Deep Learning in Cardiology
1.1 Segmentation tasks [10] suggest a new fully convolutional network architecture for the task of cardiovascular MRI segmentation. The architecture is based on the idea of network blocks in which each layer is densely connected with auxiliary side paths (skip connections) to all the following la...
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Deep Learning in Pulmonology
Deep learning has been successfully applied in various applications in pulmonary imaging, including CT registration, airway mapping, real time catheter navigation, and pulmonary nodule detection. Some of these applications are still in ongoing development, and here we review few of the most recen...
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Deep Learning in Ophthalmology
Recent works suggest novel deep learning tools for detection, segmentation and characterization of eye disorders. Accurate segmentation of retinal fundus lesions and anomalies in imaging data is an important technical step for early detection and treatment of common eye disorders, and a central a...
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Deep Learning in Brain Imaging
In this article we discuss several recent leading works about Deep Learning in brain imaging and brain microscopy. We organize the works in subsections according to the general algorithmic tasks: segmentation, registration, classification, image enhancement or other tasks. The categories are not ...
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Deep Learning in Medical Imaging
Medical imaging and medical image data analysis are rapidly growing fields. The increasing amounts of available data due to advances and ubiquity of imaging technologies give rise to new medical applications and to new requirements in existing applications, and lead to an increasing demand for ne...
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Wafer Macro Defects Detection and Classification
Defect detection is an integral part of wafer (chip) fabrication process. It enables defect detection and classification along the process to increase the fab yield (amount of good chips out of total wafers processed). Every detected defect is handled as an indicator of some process malfunction. ...
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Echo Cancellation Using Deep Learning
Complete cancellation of returned acoustic echo signal is still an unresolved issue in signal processing. When a signal from a speaker in one end of a room returns and is fed into a microphone, a delayed and distorted version of the input signal is registered and transferred to the transmitting e...
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Classification and Segmentation of Dendritic Cells
Dry eye disease (DED) is one of the most common ophthalmic disorders. Inflammation of the ocular surface is controlled by corneal antigen-presenting cells called dendritic cells (DCs), which induce T-cell activation, and play a critical role in the pathogenesis of DED. The density of corneal DC i...
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Fingerprint Segmentation Using Deep Learning
Automatic fingerprint recognition systems are based on the extraction of features from scanned fingerprint image. A successful preprocessing of the scan is an important first step towards a successful recognition, that is, comparison against a known database or the extraction of information chara...
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Intracranial Hemorrhage and Edema Segmentation
An intracranial hemorrhage (ICH) is a condition in which a blood vessel erupts inside the brain, causing internal bleeding. If not treated correctly and immediately, a brain hemorrhage can be deadly. The type of hemorrhage is usually diagnosed using a CT or MRI scan. Some hemorrhages are also acc...
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3D Cardiac MRI automatic segmentation
Massive progress in 3D Cardiac magnetic resonance imaging (MRI) gives today access to good 3D mapping of the heart, using gating to synchronize to the systolic phase of the pulse. MRI can give good distinction between the different tissues and blood without any hazard connected to radiation. 3D C...
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OCR for robots
OCR (Optical Character Recognition) modules are being used in robotics. They allow robots to understand text, an essential function in some robotic applications. OCR capability enables robots to handle items identified by imprinted text. Retail applications use robots to identify products on shel...
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Machine Vision Robots for Semiconductors
Robots have been used in the semiconductor industry for a long time. The functions of robots for semiconductors manufacturing operations are spawn over a wide range of tasks, from mechanical tasks up to intelligent tasks. The latter use machine vision. Defect detection in semiconductors manufactu...
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Robots using Machine Vision in Agriculture
Robots are widely used today in agriculture tasks. Many of these tasks require machine vision algorithms to operate successfully. The robots and their machine vision algorithms change form to best suit their function, starting from fields plowing, seeds planting, weeds handling, growth monitoring...
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Algorithms for Autonomous Driving
The transportation revolution coming with autonomous cars has already started, involving challenges that require proper handling of advanced technologies and algorithms: deep learning, to name one. . . Autonomous Driving is classified according to 5 Levels, all higher than Level Zero, where no au...
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Grading and sorting
Agricultural products are graded based on their dimensions and quality. This grade is used to sort them and assign them to different sales channels. Each item may yield better income based when properly allocated according to its exact characteristics. Usually, higher grade and bigger agricultura...
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Glaucoma Detection
Glaucoma is the second cause of blindness in the world, with over 60 million people suffering from the disease. This figure is steadily growing and most people suffering from glaucoma, even in developed countries, are not aware of their condition. Older people are at a higher risk, but glaucoma c...
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Diabetic retinopathy screening and microaneurysm detection
Diabetic Retinopathy (DR) is a leading cause of blindness, especially among adults and even more among the elderly segments of the population. It is associated with type 1 and type 2 diabetes. It occurs when high glucose levels in the blood damage blood vessels in the retinal area, leading to sma...
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