5 Pydicom Jobs

Company Description Healium Intelliscan Corporation is transforming healthcare with our cutting-edge AI-enhanced Point-of-Care Ultrasound (PoCUS) technology. Our pioneering system is designed to revolutionize the early detection of Chronic Kidney Disease (CKD) through advanced AI-backed causality predictions in its early stages. We emphasize personalized healthcare solutions by crafting customized renal blood flow models tailored to each individual. Our innovative approach aims to reduce preventable deaths associated with CKD and set a new standard in preventive healthcare. Join us in leveraging AI to redefine healthcare paradigms, ensuring a healthier future for all. Join Our AI/ML Team We are seeking a passionate Entry-Level Computer Science Engineer to join our growing team and contribute to cutting-edge medical imaging solutions. This is an excellent opportunity for a recent graduate to apply their technical skills in a real-world healthcare technology environment. What You'll Do Develop and implement computer vision algorithms for medical image analysis Build and optimize deep learning models for healthcare applications Collaborate with cross-functional teams to deliver innovative AI solutions Participate in the full software development lifecycle from research to deployment Contribute to model training, validation, and performance optimisation Required Qualifications Bachelor's degree in Computer Science, Engineering, or related field Strong proficiency in Python and object-oriented programming Basic knowledge of medical image processing (DICOM, medical imaging formats) Understanding of deep learning architectures including: ResNet (Residual Networks) Inception networks Vision Transformers (ViT) Familiarity with ML/DL frameworks (PyTorch, TensorFlow, or similar) Strong problem-solving skills and attention to detail Preferred Qualifications Experience with medical imaging libraries (SimpleITK, PyDicom, etc.) Knowledge of computer vision techniques and image preprocessing Understanding of model evaluation metrics and validation techniques Experience with version control (Git) and collaborative development Previous internship or project experience in AI/ML

AI for Early Cancer Detection (Computer Vision) Location: On-site — Kochi, Kerala, India Employment: Full-time (6–12 month contract with potential extension) Start date: Immediate ## About the project We are building a pilot AI system for early cancer detection using advanced computer vision on medical imaging. The goal is to deliver a research-grade prototype that detects and prioritizes clinically relevant findings and integrates with standardized reporting workflows, paving the way for a prospective clinical study. ## Role overview The Junior Researcher will work on-site and implement an end-to-end pipeline: data curation, preprocessing/DICOM handling, anatomical segmentation, classical candidate generation, 3D deep learning–based detection, evaluation, and a lightweight viewer for reader-in-the-loop assessment. Close mentorship and clear milestones are provided. ## Key responsibilities - Data curation - Ingest and organize de-identified imaging studies and associated labels; maintain manifests, provenance, and documentation. - Structure labels into clinically meaningful size/risk bins; handle noisy/incomplete annotations. - Algorithm development - Preprocess volumetric CT data (resampling, denoising, normalization; multi-position alignment where applicable). - Implement segmentation of relevant anatomy and classical candidate generation to reduce false positives. - Train a 3D CNN detector on candidate-centered patches with weak/semi-supervised targets; optimize sensitivity for clinically significant findings while controlling false positives per case. - Optional: add a characterization head (e.g., risk/biologic likelihood) where reliable ground truth exists. - Evaluation and reporting - Define robust patient-level splits; compute per-lesion sensitivity by size/risk, false positives per case, and per-case sensitivity. - Build simple visualization/overlays and generate standardized, clinically aligned summaries for internal review. - Document methods, code, and results; contribute to an internal white paper and potential abstract. ## Must-have qualifications - B.E./B.Tech/M.Sc./M.Tech in Computer Science, Biomedical Engineering, Data Science, or related fields. - Hands-on experience with Python, PyTorch/TensorFlow, and medical imaging toolkits (e.g., MONAI, SimpleITK, pydicom). - Practical knowledge of 3D CNNs/UNet variants, volumetric data pipelines, and GPU training workflows. - Demonstrated project in medical imaging or volumetric detection/segmentation (GitHub/portfolio or paper). - Strong experimentation hygiene: Git, reproducible environments, and clear documentation. - Willingness and ability to work on-site in Kochi, Kerala. ## Nice-to-have - Experience with CT imaging, anatomical segmentation, or classical computer vision (e.g., curvature-based candidate generation, artifact suppression). - Familiarity with radiomics and weak/semi-supervised learning for noisy labels. - Understanding of clinical reporting frameworks and screening metrics. - Experience building simple viewers (Streamlit/Gradio/ITK widgets) and robust DICOM handling. - Exposure to data governance for clinical datasets and basic biostatistics. ## What success looks like in 12 weeks - Curated and versioned imaging subsets ready for training, with label confidence tracking. - Baseline candidate generator with segmentation and measurable false-positive reduction. - 3D detection model achieving high sensitivity for clinically significant findings with controlled false positives per case. - Clear evaluation on a held-out test set and a lightweight reader-in-the-loop demo. ## Tools and stack - Python, PyTorch, MONAI, SimpleITK/pydicom, NumPy/Pandas - Experiment tracking (Weights & Biases/MLflow), Docker/conda, Git - Optional: Streamlit/Gradio for viewer, DICOMweb utilities ## What we offer - Exposure to translational research with potential publication/abstract opportunities. - Collaborative lab environment, competitive stipend, and performance-based extension. - Opportunity to impact real-world healthcare workflows. ## How to apply Email a brief note, CV, and links to relevant projects (GitHub/portfolio/papers) with subject “Junior Researcher – On-site (Kochi) – AI for Early Cancer Detection” to admin@detectiq.net Include: - A short paragraph on experience with 3D medical imaging. - One example of handling noisy or incomplete labels. - Availability and preferred start date. - Confirmation of on-site availability in Kochi. ## Application deadline Rolling review; priority for applications received within 2 weeks. Note: Prior domain-specific experience is a plus but not mandatory—strong fundamentals, curiosity, and grit matter most.

You will play a crucial role in revolutionizing medical image diagnostics by providing intelligent, ethical, and patient-centric care. We are seeking individuals with a passion for innovation and problem-solving capabilities. You should be able to empathize with consumers, address business challenges, and develop intelligent solutions. Previous experience in handling medical imaging data from various sources is essential, including a deep understanding of different image modalities such as DICOM. Proficiency in DICOM standards for imaging, communication, and reporting is a key requirement. Collaboration with annotation and PACS teams, alongside performing image preprocessing and enhancements, will be at the core of your responsibilities. Your main responsibilities will include building DICOM data pipelines, integrating them with PACS, viewers, and EMRs. You will ensure data retrieval and collation from various databases in compliance with DICOM standards. Understanding metadata, image compression, and seamless transition of parameters from DICOM to NIFTI are crucial. Your role will involve eliminating viewer and acquisition-dependent variables between image series, ensuring data homogeneity for AI model processing. Additionally, you will preprocess and enhance images, integrate AI diagnosis analyses, and work on DICOM SEG and DICOM SR nuances. Your skills and qualifications should include a strong grasp and hands-on experience with DICOM as an imaging standard, communication protocol, and reporting format. Familiarity with different medical imaging formats, DICOM SEG, and DICOM SR is required. You should possess knowledge of manufacturer-specific and machine-specific imaging differences and methodologies to resolve them. Proficiency in DICOM communication standards, DICOMWeb, and data transfer protocols is necessary. Experience with libraries like Pydicom, nibabel, SimpleITK, dcmqi, and dcm2niix will be advantageous. Moreover, you should have a comprehensive understanding of DICOM and NIFTI metadata, as well as medical imaging tests like MRI and CT. Knowledge of interoperability frameworks such as FHIR and HL7 is a plus. Strong communication, analytical, and problem-solving skills are essential, with an eagerness to adapt to new technologies. Your educational background should include a BE/B Tech degree.,

Design, develop, and maintain digital pathology and medical imaging software solutions, adhering to DICOM and related standards. Integrate and optimize AI/machine learning models within imaging workflows for tasks such as classification, segmentation, or feature extraction. Collaborate with cross-functional teams, including data scientists, clinicians, and product managers, to gather requirements and deliver high-quality solutions. Develop and support robust pipelines for image data ingestion, secure storage, retrieval, visualization, and analysis. Work with large-scale clinical and research imaging datasets, ensuring data integrity, compliance, and performance. Utilize and extend industry-standard imaging libraries and toolkits such as pydicom, OpenSlide, and ITK. Implement and maintain comprehensive software documentation, tests, and quality assurance processes. Participate in peer code reviews to ensure coding standards and best practices. Stay current with industry trends, new standards such as DICOMweb, and emerging technologies in digital pathology and AI. Contribute to the continuous improvement of engineering processes, including CI/CD pipelines and containerization strategies. Support troubleshooting, debugging, and resolution of image data and software-related issues. Ensure compliance with healthcare regulations and standards regarding data security and software quality. Mandatory Skills: Strong programming proficiency in Python. Solid understanding of DICOM and/or digital pathology standards such as WSI, DICOMweb, and HL7. Experience with medical imaging libraries or toolkits such as pydicom and OpenSlide. In-depth knowledge of AWS services, including but not limited to EC2, S3, Lambda, RDS, IAM, CloudFormation, and API Gateway. Familiarity with database technologies, whether SQL or NoSQL, for imaging data management. Experience working with large-scale image datasets, including secure storage and efficient retrieval. Understanding of version control systems such as Git. Strong skills in technical documentation and producing maintainable code. Ability to work effectively in a collaborative, multidisciplinary team environment. Excellent written and verbal communication skills. Preferred Skills: Experience developing, integrating, or deploying AI/machine learning models for medical imaging tasks such as image classification, segmentation, or feature extraction. Familiarity with deep learning frameworks such as TensorFlow, PyTorch, or Keras. Knowledge of annotation tools and data formats commonly used in pathology and imaging datasets. Experience with containerization technologies such as Docker and Kubernetes, along with cloud engineering practices. Understanding of continuous integration/continuous deployment (CI/CD) pipelines and automated testing frameworks. Prior work on whole slide imaging (WSI) workflows and digital pathology image viewers. Educational Requirements: Bachelors or masters degree in computer science or an IT-related discipline with at least 8 years of experience in the IT industry.

we are looking for a couple of senior resources (1 Lead and 1 Senior Engineer) Python Immediate Joiners Location- Bangalore The JD for the same is as below : We are seeking a highly skilled Senior Technical Lead to join our dynamic team and drive the development of cutting-edge healthcare integrations. Responsibilities: Lead and mentor a team of software developers, ensuring high-quality code and efficient project execution. Design, develop, and maintain robust Python applications, leveraging your 8+ years of experience. Utilize your expertise in DICOM libraries (pydicom, highdicom) to integrate and manage medical imaging data. Conduct thorough system design and code reviews to ensure best practices and optimal performance. Collaborate with cross-functional teams to implement healthcare integrations, enhancing interoperability and data exchange. Stay updated with the latest industry trends and technologies to continuously improve our solutions. Requirements: 8+ years of Python development experience. Proven expertise in DICOM libraries (pydicom, highdicom). Strong system design and code review skills. Experience with healthcare integrations and understanding of healthcare standards. Excellent problem-solving skills and attention to detail. Strong communication and leadership abilities. Bachelor's degree in Computer Science, Engineering, or a related field (Master's preferred). Preferred Qualifications: Experience with cloud-based solutions and microservices architecture. Familiarity with healthcare regulations and compliance standards. Knowledge of machine learning and AI applications in healthcare. Show more Show less