Muhammad Muddassir Malik
Assistant Professor in the Department of Computing
School of Electrical Engineering and Computer Science, Scholar's Avenue, NUST, H-12 Campus, Islamabad, Pakistan
M-RAD: (Currently under Development)
M-RAD (Medical Data - Research, Analysis and Development) is a research group for development of techniques and products for use in medical domain for archiving, communication, computer assisted diagnosis and visualization. We are currently working on a visualization engine to be used as a stepping stone for this project.
Tele-Surgical Training Robot and Simulator: (Currently under Development)
Developing a Surgical Simulator for Laparoscopic Surgery. Development will be be carried out using open source libraries and tools. The project is under progress in collaboration with a medical team from Holy Family Hospital, Rawalpindi. The project is funded by ICT-R&D Fund of the Govt. of Pakistan.
Related Material: Web page
Travel Visualization: (Currently under Development)
Conducting research to visualize travel patterns efficiently and expressively. Angel funding is being sought for the project.
Feature Peeling: (Completed)
In this project we present a novel rendering algorithm that analyses the ray profiles along the line of sight for visualizing MRI and CT datasets. The profiles are subdivided according to encountered peaks and valleys at so called transition points. The sensitivity of these transition points is calibrated via two thresholds. The slope threshold is based on the magnitude of a peak following a valley, while the peeling threshold measures the depth of the transition point relative to the neighboring rays. This technique separates the dataset into a number of feature layers.
Computation and Visualization of Fabrication Artifacts
In this project we propose a novel technique to measure fabrication artifacts through direct comparison of a reference surface model with the corresponding industrial CT volume. Our technique uses the information from the surface model to locate corresponding points in the CT dataset. We then compute various comparison metrics to measure differences (fabrication artifacts) between the two datasets. The differences are presented to the user both visually as well as quantitatively.
Locally Adaptive Marching Cubes through Iso-value Variation
We present a locally adaptive marching cubes algorithm. It is a modification of the marching cubes algorithm where instead of a global iso-value each grid point has its own iso-value. This defines an iso-value field, which modifies the case identification process in the algorithm. The marching cubes algorithm uses linear interpolation to compute intersections of the surface with the cell edges. Our modification computes the intersection of two general line segments, because there is no longer a constant iso-value at each cube vertex. An iso-value field enables the algorithm to correct biases within the dataset like low frequency noise, contrast drifts, local density variations and other artefacts introduced by the measurement process. It can also be used for blending between different isosurfaces (e.g., skin, veins and bone in a medical dataset).
Improvement of X-Ray image acquisition using a GPU based 3DCT simulation tool
In this project we present a simulation tool for industrial X-Ray computed tomography (CT) systems which is able to predict the results of real measurements. Such a prediction helps the technician in measurement technology to minimize artefacts by using optimal measurement parameters and therefore it helps to get more accurate results. The presented simulation software offers an implementation for CPU’s and GPU’s.
Related Material: Document
Comparative Visualization for Parameter Studies of Dataset Series
In this project we propose comparison and visualization techniques to carry out parameter studies for the special application area of dimensional measurement using 3D X-ray computed tomography (3DCT). A dataset series is generated by scanning a specimen multiple times by varying parameters of an industrial 3DCT device. A high-resolution series is explored using our planar-reformatting-based visualization system. We present a novel multi-image view and an edge explorer for comparing and visualizing gray values and edges of several datasets simultaneously. Visualization results and quantitative data are displayed side by side. Our technique is scalable and generic. It can be effective in various application areas like parameter studies of imaging modalities and dataset artifact detection.
Parallel Processor Matrix multiplication and Load Balancing
SPTA implementation for a bridged LAN
Distributed Flight Reservation System