Loading
Software that draws organs and tumours on scans automatically, saving hours per patient and making daily plan adaptation practical.
Deep-learning segmentation of organs at risk and targets (Limbus AI, MIM Software, TheraPanacea, Siemens AI-Rad Companion Organs RT, Varian Ethos and Elekta's ADMIRE, MVision, Carina) is now routine in radiotherapy departments and FDA-cleared for dozens of structures. Target-volume contouring remains physician-reviewed. Online adaptive radiotherapy (Ethos, Unity) depends on it to re-plan in minutes.
Convolutional and transformer networks trained on expert contours segment CT/MR; outputs are edited and approved by clinicians.
Nothing in the corpus depends on this yet.
Dependencies are what this technology cannot be delivered without: manufacturing steps, instruments, software, upstream methods. See its full chain on the map.
One technology page on OnCo cites this paper by its DOI; this record gives the citation a page of its own so a reader can follow it without leaving OnCo. Read the abstract above alongside the citing page listed under Related; the record was created automatically from the Europe PMC entry and its figures have not been checked by hand.
Variation between clinicians in drawing the target is one of the largest errors in radiotherapy and one of the least measured in terms of what it does to patients. The field has studied whether outlines differ far more than whether the differences matter.
Query for this technology: (TITLE:"AI auto-contouring and adaptive planning" OR ABSTRACT:"AI auto-contouring and adaptive planning") AND (cancer OR tumor OR tumour OR oncology OR carcinoma OR lymphoma OR leukemia OR leukaemia OR myeloma OR sarcoma OR melanoma OR glioma). Results are unfiltered search hits about AI auto-contouring and adaptive planning, not a curated reading list.
Shares AI compute and model platforms for oncology, AI in oncology roadmap: pattern readers → foundation models → agents in the workflow and the tag supporting.
Shares AI compute and model platforms for oncology and the tag supporting.
Shares Adaptive radiotherapy (online replanning), MR-guided adaptive radiotherapy, Radiotherapy roadmap: X-rays → shaped beams → fewer fractions, particles and FLASH, IMRT / IGRT (modern external beam) and the tag precision.
Shares Uncertainties in volume delineation in radiation oncology: a systematic review and recommendations for future studies, Variation between clinicians in drawing the radiotherapy target, Adaptive radiotherapy (online replanning), IMRT / IGRT (modern external beam) and the tag precision.
Shares AI compute and model platforms for oncology and the tag supporting.
Shares IMRT / IGRT / VMAT (modern external beam radiotherapy) and the tag precision.
Shares Radiotherapy treatment planning and QA software and the tag supporting.
Shares Radiotherapy treatment planning and QA software and the tag supporting.
Open-source projects that implement or serve this technology, from OnCo's own catalogue: licence and last activity as the repository reported them on the day of the fetch. Listing is not endorsement; check the licence before reuse and the validation before clinical use.
The self-configuring segmentation method from DKFZ that wins most medical segmentation challenges out of the box, including brain, kidney and liver tumour tasks.
The PyTorch framework for deep learning in medical imaging, co-founded by NVIDIA and King's College London, used for tumour segmentation and detection research and products.
Segment Anything adapted to medical images across modalities, with released weights.
Segments over a hundred anatomical structures in CT and MRI in one command, widely used for organs at risk and body composition.
An intelligent annotation server that plugs into 3D Slicer, OHIF and QuPath to speed up labelling with active learning.
Microsoft's foundation model that segments, detects and recognises objects across nine imaging modalities from a text prompt.
Processing library and tools for radiotherapy imaging: auto-segmentation of cardiac substructures, registration and DICOM-RT handling.
The Kidney Tumor Segmentation challenge repository: data access code and baselines for CT kidney and tumour segmentation.
Commercial and regulated products that serve this technology. Each card says what is behind it: a regulator's database, the literature, a public body's list, or only the company's own words. Listing is not endorsement, and a clearance is a regulatory fact, not a clinical one.
A treatment planning system for photons, protons and ions, with deep-learning segmentation and planning built in and a large physics literature behind it.
A family of reading algorithms for CT and MR, including organ contouring for radiotherapy and prostate MR reading.
Automatic contouring sold alongside a set of plan checking tools, aimed at the time a physicist spends on routine work.
MIM's deep-learning contouring product, cleared separately from the rest of the suite.
A modular planning suite for cranial radiosurgery and stereotactic treatment, including automatic segmentation and multiple-metastasis planning.
The planning and adaptation software behind online adaptive radiotherapy, which re-plans on the day's image while the patient is on the couch.
Every source this page cites, grouped by who published it. Grouping is read from the web address, not assigned by hand.
A source that has moved or gone is reported by the weekly link check. /audit/
