Sepand Soltani

Sepand AliMadadSoltani

Lyon, France | +33 (0)6 49 55 25 42
sepand.alimadadsoltani@etu.univ-lyon1.fr | https://sepandsoltani.github.io

Education

University of Claude Bernard | Polytech Lyon Lyon, France
Master II in Medical Device Engineering Fall 2024-Present
Excellence Scholarship Recipient (10,000€)
Courses: MRI, Segmentation & Registration, ML/AI in Medical Images, Image Reconstruction & Inverse Problems

K.N. Toosi University of Technology Tehran, Iran
4 Year Bachelor of Science in Electrical Engineering 2018-2023
Concentration: Biomedical Engineering
GPA: 16.33/20 (Last two years: 17.29/20)
Courses:Statistical Pattern Recognition, Signals & Systems

Research Interests

MRI
PET
Functional Imaging
Medical Image Segmentation
Machine Learning and Artificial Intelligence in Health

Research Experience

Estimation of Image-Derived Input Function in Dynamic Brain PET Imaging Lyon, France
CERMEP November 2024-Present

Conducted a state-of-the-art literature review
Conducted pre-processing steps on MRI and PET images to ensure data quality and consistency
Developed a robust segmentation algorithm for accurate extraction of internal carotid arteries from MR angiography images
Implemented different Partial Volume Correction algorithms for obtaining accurate input function
Evaluated method performance across multiple datasets using various PET quantification models

Interactive and Intelligent Tissue Boundary Segmentation Tool Tehran, Iran
MVMIP, KNTU Spring-Summer 2023

Developed a Python-based medical image analysis software, from scratch utilizing Python, VTK, and PyQt libraries
Implemented multiple interactive tools (ruler, shapes, and text insertion tools)
Developed an image processing algorithm for tissue boundary detection and integrated it in a smart interactive scissor tool for fast semi-automatic tissue segmentation
Enabled users to import custom plugins to extend the functionality of the software based on their needs
Successfully shipped the software for Linux and Windows operating systems

Skills

Programming: Python, C++, CMake, Bash, MATLAB, QML
Software and Tools: GNU/Linux, Git, FMRIB FSL, NiftyReg, dcm2niix, TCCPLIB
Libraries: Tensorflow, PyTorch, NumPy, pandas, scikit-learn, Matplotlib, ITK, VTK, Qt, PyQt
Languages: Persian (Native), English (TOEFL: Overall: 101/120, R: 27, L:27, S:23, R:24), French (Beginner-A2)

Projects

Image-based Persian and English Character Sequence Recognition using Recurrent Convolutional Neural Networks(RCNN)

Winter 2023

Implemented the network based on a paper using the Tensorflow library in Python
Synthesized images of Persian text of different variety
Applied data augmentation techniques such as rotating, translating, adding distortion, and adding noise to images
Successfully trained the model for both languages using the self-made synthesized Persian dataset and public English datasets
Achieved +85% accuracy for both languages

Exploring Possibility of Alzheimer's Disease Detection using Deep Neural Network based on fMRI Functional Connectivity Maps and Time-series Data

Fall 2022-Winter 2023

Pre-processed and processed raw fMRI and MRI data from the ADNI database using the FSL library to extract time-series data to calculate functional connectivity maps of the subjects' brains
Studied the previous works on this subject to find the gap
Experimented with RCNN & CNN networks using Tensorflow to extract temporal and spatial features from images
Gained hands-on experience with image pre-processing, neural network architecture, and deep learning principles
Although a full model was not achieved, a lot of experience and insight were gained into medical imaging and deep learning concepts deep learning concepts

Automated fMRI Pre-processing and Time-series Extraction Pipeline for Large Datasets using FSL in Python

Summer 2022

Implemented brain extraction from structural reference MR image
Implemented fMRI pre-processing including motion correction, slice timing correction, spatial smoothing, and co-registration
Implemented atlas-based ROI time-series extraction
Enabled parallel processing to accelerate computation for large datasets
Utilized the program for processing fMRI data from the ADNI dataset

The Game of Tetris with a Custom Game Engine Using OpenGL in C++

Spring 2022

Developed a custom 2D graphics renderer completely from scratch using the OpenGL graphics API in C++
Implemented user input handling, navigatable menus, and text rendering capabilities to the engine
Designed and implemented the game of Tetris using the said engine in Object Oriented C++

Work Experience

NTH

Tehran, Iran

Oct 2023-July 2024

Designed and developed a modern interface using the Qt Framework's QML language
Built and optimized backend logic in C++ to handle large volumes of data efficiently

TECVICO

Vancouver, Canada (Remote)

Summer 2023

Created a Python-based medical analysis software focusing on user-friendliness and user experience
Designed and implemented a workflow user interface for bioinformatics analysis and processing using the Qt framework
Worked with a team of engineers to integrate various machine learning algorithms into the workflow
Designed and integrated a medical image visualizer using VTK
Integrated multiple visualization tools and pipelines such as colormaps, image thresholding and interactive segmentation

Razeq Co.