Classification of Volumetric Images Using Multi-Instance Learning and Extreme Value Theorem


Medical practitioners use volumetric imaging as a diagnostic tool. Popular approaches such as convolutional neural networks (CNN) can only be used for volumetric Image Processing if training data and GPU memory are readily available. During the training phase, the volumetric image classification problem is posed as a multi-instance classification problem and a unique strategy is proposed to adaptively select positive instances from positive bags of positive examples These images without a pathology are modelled using the extreme value theory and then used to detect positive occurrences of a pathology. Using three separate image classification tasks (i.e., classify retinal OCT images according to the presence or absence of fluid buildups in retinal OCT images, pulmonary 3D-CT images, and histopathology 2D images) the experimental results show that the proposed method produces classifiers with similar performance to fully supervised methods and achieves the state of the art performance in all examined test cases..

Did you like this research project?

To get this research project Guidelines, Training and Code... Click Here

PROJECT TITLE :Multi-Instance Learning with Discriminative Bag Mapping - 2018ABSTRACT:Multi-instance learning (MIL) could be a helpful tool for tackling labeling ambiguity in learning as a result of it allows a bag of instances
PROJECT TITLE : Multi-Core Embedded Wireless Sensor Networks Architecture and Applications - 2014 ABSTRACT: Technological advancements in the silicon industry, as predicted by Moore's law, have enabled integration of billions
PROJECT TITLE : Efficient Data Collection for Large-Scale Mobile Monitoring Applications - 2014 ABSTRACT: Radio frequency identification (RFID) and wireless sensor networks (WSNs) have been popular in the industrial field,
PROJECT TITLE : Cross-Layer Approach for Minimizing Routing Disruption in IP Networks - 2014 ABSTRACT: Backup paths are widely used in IP networks to protect IP links from failures. However, existing solutions such as the commonly
PROJECT TITLE :Network Traffic Classification Using Correlation Information - 2013ABSTRACT:Traffic classification has wide applications in network management, from security monitoring to quality of service measurements. Recent

Ready to Complete Your Academic MTech Project Work In Affordable Price ?

Project Enquiry