Posts by Soumitra Chatterjee
Bringing the MONAI Model Zoo to AMD Instinct™ GPUs: Validated Inference on ROCm
- 30 October 2026
The Medical Open Network for AI (MONAI) Model Zoo is often the first stop when a researcher is building a medical imaging application: a shared shelf of ready-to-use, peer-reviewed models, where you can find a whole-body computed tomography (CT) segmenter or an interactive annotation network already trained, packaged, and ready to run.
Accelerating MONAI Digital-Pathology Pipelines on AMD Instinct™ GPUs with hipCIM
- 26 October 2026
A digital-pathology model is only as fast as the pipeline that feeds it. That’s simple to overlook when the conversation turns to network architectures and FLOPs, but on real whole-slide workloads the truth is stubborn: a great deal of the wall-clock time goes to reading gigapixel slides off disk and decoding them into the small tiles the model consumes. Speed up the model and leave the reader untouched, and the pipeline barely moves.
hipCIM 26.06: GPU-Accelerated Whole-Slide Image I/O on AMD Instinct™ GPUs
- 20 October 2026
Every whole-slide image tells a story in pixels. A whole-slide image is a glass pathology slide scanned into a single very large digital image, stored as a pyramid of small tiles so a viewer can pan and zoom it. A single biopsy digitized at 20× magnification can span tens of thousands of pixels on each side and weigh in at several gigabytes. Before a model can learn anything from that slide, something has to read it off disk, decode its thousands of small JPEG-compressed tiles, and turn them into tensors the accelerator can work on. In digital pathology, that unglamorous first step is often where the wall-clock time quietly disappears.
Announcing MONAI 1.0.0 for AMD ROCm: Breakthrough AI Acceleration for Medical Imaging Models on AMD Instinct™ GPUs
- 07 October 2025
Today, AMD is thrilled to announce MONAI 1.0.0 for AMD ROCm, now available to the community as part of the ROCm-LS Early Access release. In this blog you will learn how to use MONAI to load an analyze medical images, and see results from more advanced case studies.
Introducing ROCm-LS: Accelerating Life Science Workloads with AMD Instinct™ GPUs
- 18 July 2025
AMD is thrilled to announce the early access release of ROCm-LS (ROCm Life Science), a new cutting-edge software toolkit designed to accelerate life science computational workloads on AMD Instinct™ GPUs. ROCm-LS joins ROCm-DS as a part of AMD’s new family of toolkits aimed at providing powerful solutions to real world problems. Similar to ROCm-DS, ROCm-LS is built upon the established ROCm software ecosystem, offering a collection of components and libraries that address the pressing needs of the life science community. The early access release of ROCm-LS enables you to experiment with accelerating your life science workloads, such as digital pathology, automated medical image analysis, and feature extraction and enhancement in large TIFF files on AMD Instinct GPUs. Join us in exploring this tantalizing glimpse into the future capabilities of ROCm-LS, setting the stage for the next evolution in life science computing.
Announcing hipCIM: A Cutting-Edge Solution for Accelerated Multidimensional Image Processing
- 18 July 2025
In the rapidly evolving landscape of data science and computational imaging, hipCIM 1.0.0 introduces a powerful, GPU-accelerated open-source library that redefines multidimensional image processing for life sciences, biomedical research, and computational imaging. This open-source, accelerated software library redefines how multidimensional datasets are processed, offering unparalleled capabilities across scientific fields such as biomedical imaging, geospatial analytics, material sciences, life sciences, and remote sensing to name a few. With the initial release of hipCIM 1.0.0, AMD enters the arena, ready to push the boundaries of life science research and stand at the forefront of a new era in multidimensional image processing.