You will get medical image segmentation using Python and deep learning
Project details
I will help you analyze medical images using Python and deep learning techniques. I provide image preprocessing, enhancement, segmentation, visualization, and quantitative evaluation workflows for biomedical imaging applications.
The workflow includes data inspection, preprocessing and normalization, AI-based image analysis, performance evaluation, and delivery of clean code with documentation. I can work with microscopy images, histopathology images, and other biomedical image datasets.
You will receive an organized analysis pipeline, visual results, evaluation metrics, and reproducible documentation suitable for research, prototyping, or further development.
The workflow includes data inspection, preprocessing and normalization, AI-based image analysis, performance evaluation, and delivery of clean code with documentation. I can work with microscopy images, histopathology images, and other biomedical image datasets.
You will receive an organized analysis pipeline, visual results, evaluation metrics, and reproducible documentation suitable for research, prototyping, or further development.
AI Development Type
Deep Learning, Model TuningAI Tools
Azure Machine Learning, deeplearn.js, Deeplearning4j, MATLAB, NVIDIA AI Platform, OpenCV, PyBrain, PyTorch, Sonnet, TensorFlowAI Development Language
PythonWhat's included
| Service Tiers |
Starter
$150
|
Standard
$250
|
Advanced
$400
|
|---|---|---|---|
| Delivery Time | 3 days | 7 days | 14 days |
Number of Revisions | 1 | 2 | 2 |
AI Model Integration | - | - | |
Detailed Code Comments | |||
Knowledge Graph | - | - | - |
Model Documentation | - | ||
Ontology | - | - | - |
Source Code | - | ||
Taxonomy | - | - | - |
Frequently asked questions
About Mysunat
AI/ML Engineer | Computer Vision, Deep Learning & Data Analysis
Dhaka, Bangladesh - 8:28 am local time
I develop machine learning, computer vision, data-analysis, and intelligent-system solutions using Python, PyTorch, TensorFlow, R, and MATLAB, with particular experience in healthcare and biomedical applications.
My expertise includes:
✅ Medical image preprocessing and segmentation
✅ Deep learning model development (U-Net, CNNs, PyTorch)
✅ Biomedical data analysis and visualization
✅ Bioinformatics and transcriptomic data analysis
✅ Biosignal processing and feature extraction
✅ Statistical analysis and publication-ready results
✅ Biomedical sensor and digital-twin prototyping (ESP32, IoT)
Selected project experience:
🧬 Medical Image AI
* Developed a five-fold nuclei segmentation pipeline using U-Net-based models with image normalization and evaluation using Dice, IoU, and recall metrics.
🧪 Computational Biology
* Performed cancer transcriptomic analysis using differential expression, network analysis, and validation workflows in R.
🩺 Biomedical Systems
* Developed ESP32-based gait monitoring systems using IMU and FSR sensors.
* Built neuromechanical models and interactive digital-twin implementations for rehabilitation applications.
Clients receive:
✅ Clean and organized code
✅ Reproducible analysis workflows
✅ Clear documentation
✅ Scientific interpretation of results
Whether you have a dataset, research problem, or biomedical prototype idea, I can help design and implement a practical technical solution.
Steps for completing your project
After purchasing the project, send requirements so Mysunat can start the project.
Delivery time starts when Mysunat receives requirements from you.
Mysunat works on your project following the steps below.
Revisions may occur after the delivery date.
Dataset Review & Preprocessing
I will review the provided medical images, inspect data quality, and perform necessary preprocessing such as resizing, normalization, enhancement, and preparation for analysis.
AI-Based Image Analysis
I will apply suitable computer vision or deep learning techniques for medical image analysis, including segmentation workflows when required.