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Found 11 papers, 0 papers with code
Deep Learning for Improved Polyp Detection from Synthetic Narrow-Band Imaging
This paper first shows that better results for polyp detection can be achieved on NBI compared to a relatively similar dataset of WLI.
A Multi-channel EEG Data Analysis for Poor Neuro-prognostication in Comatose Patients with Self and Cross-channel Attention Mechanism
This work investigates the predictive potential of bipolar electroencephalogram (EEG) recordings towards efficient prediction of poor neurological outcomes.
Multimodal Deep Learning for Personalized Renal Cell Carcinoma Prognosis: Integrating CT Imaging and Clinical Data
The feature extractor module, based on the 3D CNN architecture, predicts the ISUP grade of renal cell carcinoma tumors linked to mortality rates from CT images.
Accurate Real-time Polyp Detection in Videos from Concatenation of Latent Features Extracted from Consecutive Frames
We propose an efficient feature concatenation method for a CNN-based encoder-decoder model without adding complexity to the model.
Non-invasive Waveform Analysis for Emergency Triage via Simulated Hemorrhage: An Experimental Study using Novel Dynamic Lower Body Negative Pressure Model
The extent to which advanced waveform analysis of non-invasive physiological signals can diagnose levels of hypovolemia remains insufficiently explored.
Simple U-net Based Synthetic Polyp Image Generation: Polyp to Negative and Negative to Polyp
In this study, we propose a deep learning-based polyp image generation framework that generates synthetic polyp images that are similar to real ones.
The End-to-End Molecular Communication Model of Extracellular Vesicle-based Drug Delivery
A closer look at nature has recently brought more interest in exploring and utilizing intra-body communication networks composed of cells as intrinsic, perfectly biocompatible infrastructures to deliver therapeutics.
Molecular Communications in Viral Infections Research: Modelling, Experimental Data and Future Directions
Hundreds of millions of people worldwide are affected by viral infections each year, and yet, several of them neither have vaccines nor effective treatment during and post-infection.
Polyp Detection and Segmentation using Mask R-CNN: Does a Deeper Feature Extractor CNN Always Perform Better?
Automatic polyp detection and segmentation are highly desirable for colon screening due to polyp miss rate by physicians during colonoscopy, which is about 25%.
Automatic Colon Polyp Detection using Region based Deep CNN and Post Learning Approaches
Automatic detection of colonic polyps is still an unsolved problem due to the large variation of polyps in terms of shape, texture, size, and color, and the existence of various polyp-like mimics during colonoscopy.
Abnormal Colon Polyp Image Synthesis Using Conditional Adversarial Networks for Improved Detection Performance
In this paper, we propose a framework of conditional adversarial networks to increase the number of training samples by generating synthetic polyp images.
