A single level machine-learnt classifier is used in medical imaging. A gross or large structure is located using any approach, including non-ML approaches such as region growing or level-sets. Smaller portions of the structure are located using ML applied to relatively small patches (small relative to the organ or overall structure of interest). The classification of small patches allows for a simple ML approach specific to a single scale or at a voxel/pixel level. The use of small patches may allow for providing classification as a service (e.g., cloud-based classification) since partial image data is to be transmitted. The use of small patches may allow for feedback on classification and updates to the ML. The use of small patches may allow for the creation of a labeled library of classification partially based on ML. Given a near complete labeled library, a simple matching of patches or a lookup can replace ML classification for faster throughput.