This study presents an end-to-end tendon pathology detection (classification) module utilizing a custom ankle MRI dataset comprising 76 subjects (45 healthy, 31 pathological). We propose a graph-based module that converts images into graph representations for classification.
The main goal of this project was to develop tissue (WM, GM, and CSF) segmentation methods in brain MRI images. The dataset used is IBSR18, which contains 18 skull-stripped and bias field-corrected T1-w images with different spatial resolutions (pixel spacing), and there is a heterogeneity in image intensities that hinders segmentation. System architecture used - Data → Pre-processing → Segmentation (3D patch-wise segmentation using 3D U-Net).
The main objective of this project was to design a computer-aided diagnosis system to develop a deep learning algorithm for diagnosis in histological patches to classify benign vs malignant patches. System architecture used - Image → Normalization → Per instance standardization → Aggressive Data Augmentation → Classification.
The main goal of this project was to design a computer-aided diagnosis system to classify dermoscopic images and determine whether any case belongs to Nevus or lesion. System architecture - Image → Normalization → Per instance standardization → Aggressive Data Augmentation → Classification.
This project aims to register 3D CT lung images, which was tested on the first 4 cases available on 4DCT DIR-Lab Challenge. Where data is available with 300 landmark annotations. Evaluation is made using TRE 3D Euclidean distance between transformed landmarks.
The goal of this project was to demonstrate pedicle screw placement for spine fusion. Steps - 1) Trajectory planning (Type of movement is Point to point), 2) Software simulation of robotic spine surgery (Stäubli Robotics Suite), and 3) Testing demo surgery using Tx60 Stabuli.
The main aim of this project was to design a computer-aided diagnosis system that can detect mass/masses in mammograms to help the screening procedure. System architecture - Image → Candidate extraction → Feature extraction → Classification.
This project proposes a discrete image reconstruction algorithm using parallel beam geometry where a set of X-ray beams are passed through the object of interest and intensity variations of the beams at input and output are measured. To reconstruct, filtered back projection is used, which uses a 1D filter on the projection data before back projecting (2D or 3D) the data onto the image space.
The VIZN application provides an environment where users will be able to test some performance related to the eyesight, observing the evolution over time by means of innovative user controls. In this project, all the tests were prepared in a scientific way.
The purpose of this project was to design an Inverse Kinematic controller for the Kinova Jaco2 robot to follow some given tasks. The control objectives include position only without exploiting the redundancy, given by both the position and the orientation, the end-effector orientation needs to be changed, and the redundancy needs to be exploited by maximizing the manipulability.