cspsofttech

IEEE Medical Imaging projects for Engineering students-M.Tech, B.Tech, BE, MSC, MCA, Diploma Students

Matlab/ Python/NS2/ Java/Dot Net Medical Imaging projects with source code and IEEE papers

Medical imaging is the technique and process of imaging the interior of a body for clinical analysis and medical intervention, as well as visual representation of the function of some organs or tissues.

CODE	TITLE	OUTPUT
MI 01	A Deep Cascade of Convolutional Neural Networks for Dynamic MR Image Reconstruction
MI 02	A Skeletal Similarity Metric for Quality Evaluation of Retinal Vessel Segmentation
MI 03	Anatomically Constrained Neural Networks (ACNNs) Application to Cardiac Image Enhancement and Segmentation
MI 04	Convolutional Invasion and Expansion Networks for Tumor Growth Prediction
MI 05	End-to-End Adversarial Retinal Image Synthesis
MI 06	Estimating Dynamic Connectivity States in fMRI Using Regime-Switching Factor Models
MI 07	Image Segmentation Using Disjunctive Normal Bayesian Shape and Appearance Models
MI 08	Magnetic Resonance RF Pulse Design by Optimal Control with Physical Constraints
MI 09	Multimodal MR Synthesis via Modality-Invariant Latent Representation
MI 10	Robust Unmixing of Dynamic Sequences Using Regions of Interest
MI 11	Single- and Multiple-Shell Uniform Sampling Schemes for Diffusion MRI Using Spherical Codes
MI 12	Sparse Representation-Based Radiomics for the Diagnosis of Brain Tumors
MI 13	Synergistic PET and SENSE MR Image Reconstruction Using Joint Sparsity Regularization
MI 14	Tumor cell load and heterogeneity estimation from diffusion-weighted MRI calibrated with histological data an example from lung cancer

CODE

TITLE

OUTPUT

MI 01

A Deep Cascade of Convolutional Neural Networks for Dynamic MR Image Reconstruction

MI 02

A Skeletal Similarity Metric for Quality Evaluation of Retinal Vessel Segmentation

MI 03

Anatomically Constrained Neural Networks (ACNNs) Application to Cardiac Image Enhancement and Segmentation

MI 04

Convolutional Invasion and Expansion Networks for Tumor Growth Prediction

MI 05