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Found 21 papers, 2 papers with code
Adaptive search area for fast motion estimation
This search area is similar to that of the full search (FS) algorithm but smaller for most blocks of a frame.
Gland Segmentation in Histopathology Images Using Deep Networks and Handcrafted Features
Histopathology images contain essential information for medical diagnosis and prognosis of cancerous disease.
Fetal Ultrasound Image Segmentation for Measuring Biometric Parameters Using Multi-Task Deep Learning
Ultrasound imaging is a standard examination during pregnancy that can be used for measuring specific biometric parameters towards prenatal diagnosis and estimating gestational age.
ReDMark: Framework for Residual Diffusion Watermarking on Deep Networks
Due to the rapid growth of machine learning tools and specifically deep networks in various computer vision and image processing areas, application of Convolutional Neural Networks for watermarking have recently emerged.
Multiple Abnormality Detection for Automatic Medical Image Diagnosis Using Bifurcated Convolutional Neural Network
In recent years portable medical imaging devices such as capsule endoscopy and digital dermatoscope have been introduced and made the diagnosis procedure easier and more efficient.
Segmentation of Bleeding Regions in Wireless Capsule Endoscopy for Detection of Informative Frames
Both CNN and MLP structures are simplified to reduce the number of computational operations.
Adaptive specular reflection detection and inpainting in colonoscopy video frames
In the detection phase, we employ both HSV and RGB color space information for segmentation of specular reflections.
Left ventricle segmentation By modelling uncertainty in prediction of deep convolutional neural networks and adaptive thresholding inference
Deep neural networks have shown great achievements in solving complex problems.
Lossless Image Compression Algorithm for Wireless Capsule Endoscopy by Content-Based Classification of Image Blocks
Recent advances in capsule endoscopy systems have introduced new methods and capabilities.
Lossless Compression of Angiogram Foreground with Visual Quality Preservation of Background
By increasing the volume of telemedicine information, the need for medical image compression has become more important.
Reversible Image Watermarking for Health Informatics Systems Using Distortion Compensation in Wavelet Domain
In this study a reversible watermarking is investigated with focusing on increasing the embedding capacity and reducing the distortion in medical images.
Left Ventricle Segmentation in Cardiac MR Images Using Fully Convolutional Network
In this paper we propose an automated method for segmenting the left ventricle in cardiac MR images.
Segmentation of Bleeding Regions in Wireless Capsule Endoscopy Images an Approach for inside Capsule Video Summarization
Wireless capsule endoscopy (WCE) is an effective means of diagnosis of gastrointestinal disorders.
Liver segmentation in CT images using three dimensional to two dimensional fully convolutional network
The need for CT scan analysis is growing for pre-diagnosis and therapy of abdominal organs.
Liver Segmentation in Abdominal CT Images by Adaptive 3D Region Growing
In this paper, we propose an adaptive 3D region growing with subject-specific conditions.
Deep Learning in Pharmacogenomics: From Gene Regulation to Patient Stratification
This Perspective provides examples of current and future applications of deep learning in pharmacogenomics, including: (1) identification of novel regulatory variants located in noncoding domains and their function as applied to pharmacoepigenomics; (2) patient stratification from medical records; and (3) prediction of drugs, targets, and their interactions.
Dense Pooling layers in Fully Convolutional Network for Skin Lesion Segmentation
One of the essential tasks in medical image analysis is segmentation and accurate detection of borders.
Vessel Segmentation and Catheter Detection in X-Ray Angiograms Using Superpixels
In this framework we use our catheter detection and tracking method which detects the catheter by finding its ridge in the first frame and traces in other frames by fitting a second order polynomial on it.
Blind Stereo Image Quality Assessment Inspired by Brain Sensory-Motor Fusion
Then, a stacked neural network model is proposed, which learns the extracted features and accurately evaluates the quality of stereo images.
Hand Gesture Recognition for Contactless Device Control in Operating Rooms
In this paper we introduce a system of hand gesture recognition based on a deep learning approach.
Extraction of Skin Lesions from Non-Dermoscopic Images Using Deep Learning
The input image is preprocessed and then its patches are fed to a convolutional neural network (CNN).
