Rejected from IEEE TMI? The 7 Best Venues to Submit Next

Your closest matches depend on whether the contribution is methodology, a clinical or informatics study, a device or systems result, or a general image-processing advance. The shortlist below covers all four routes.

Source: Clarivate JCR 2024, IEEE, Elsevier, RSNA, and AAPM author and open-access pages (accessed June 2026). APCs are list prices excluding tax and may be reduced at submission.

Run a IEEE Transactions on Medical Imaging manuscript fit check before you pick a venue, so you route on the actual rejection reason rather than on prestige alone.

1. Medical Image Analysis. This is the closest non-IEEE match for a genuine medical-imaging methodology paper, and it holds a comparable selectivity bar. If IEEE TMI judged your work "good but not a methodology advance for us," MedIA often reads it more favorably when the method is strong and the validation is thorough, because the journal frames the same contribution as image analysis rather than against IEEE TMI's strict methods-only bar.

2. IEEE Journal of Biomedical and Health Informatics. The right home when the real contribution is clinical decision support, multimodal patient data, or a health-informatics question rather than a new imaging method. JBHI is the sister IEEE title most TMI editors name when a paper is more clinical than methodological.

3. IEEE Transactions on Biomedical Engineering. Best when the work centers on a device, an instrument, a signal-processing pipeline, or a systems-level result. TBME's scope is broader than imaging, so a paper whose center of gravity is engineering, not the imaging methodology, fits its bar better.

4. IEEE Transactions on Image Processing. Reach for this when the advance is a general image-processing method that happens to be demonstrated on medical data. TIP rewards the algorithmic and theoretical contribution on its own terms, and a method that generalizes beyond one modality is judged on the imaging science, not the clinical claim.

5. Radiology: Artificial Intelligence. The strongest route when your paper is a clinically validated AI study: external validation, reader studies, or evidence that the model changes a radiologist's decision. RSNA's review is clinically rigorous, so this fits work whose contribution is the validated clinical use, not the network architecture.

6. Computerized Medical Imaging and Graphics. A solid mid-tier Elsevier landing spot for a competent applied method or a computer-aided-diagnosis pipeline that did not clear IEEE TMI's novelty bar. The bar is more forgiving and the scope match is direct.

7. Medical Physics. The natural home when the contribution is quantitative imaging, reconstruction physics, dosimetry, or imaging quality assurance. If the physics or the measurement is the protagonist rather than a learned model, Medical Physics frames it well.

The single most important decision after an IEEE TMI rejection is not which journal sits one tier down. It is whether your paper is a methodology paper at all, and whether you understood that IEEE will not move it for you.

First, know that IEEE has no automatic transfer. Elsevier runs the Article Transfer Service and Nature runs a portfolio cascade, where a rejecting editor offers a one-click move that carries your files and reviews. IEEE has no equivalent.

An IEEE TMI Associate Editor may suggest a sister title in the decision letter, IEEE Journal of Biomedical and Health Informatics, IEEE Transactions on Biomedical Engineering, or IEEE Transactions on Medical Robotics and Bionics, but you resubmit manually through that journal's own ScholarOne site. Treat the suggestion as a routing hint, not a transfer, and reformat to the new template before you resubmit.

Second, decide the methodology-versus-application route. IEEE TMI rewards a method the field can reuse. If it rejected you because the contribution is "a known architecture applied to a new task," the honest read is that the paper is application-shaped. In that case the next venue is a clinically framed journal (Radiology: Artificial Intelligence for a validated study) or an applied venue (Computerized Medical Imaging and Graphics), not a methods-only journal where the same "where is the new method?" objection resurfaces.

Third, step down by fit, not just by prestige rank. For a genuine imaging-methods advance, the first-choice cascade is Medical Image Analysis, then IEEE Transactions on Image Processing for a general algorithmic result. For a clinical or informatics center of gravity, IEEE Journal of Biomedical and Health Informatics. For a device or systems result, IEEE Transactions on Biomedical Engineering. For a quantitative-imaging or physics contribution, Medical Physics. Each step trades a little selectivity for a better scope match, which matters more than the raw number.

Source: IEEE TMI author guidance plus IEEE, Elsevier, RSNA, and AAPM venue scope pages (accessed June 2026).

In our pre-submission review work with IEEE Transactions on Medical Imaging manuscripts, the rejections we see most often cluster into four named patterns. Each is journal-specific, testable against your own manuscript, and tied to a component a reviewer can point at. Across our IEEE TMI pre-submission reviews, these four map to one recurring editorial expectation: a medical-imaging methodology advance, fully validated, inside a strict page limit.

The application paper wearing a methodology label. This is the most common pattern in the IEEE TMI submissions we review. The manuscript takes an existing architecture, a U-Net, a transformer, a diffusion model, and applies it to a new modality or organ, with the abstract framing a Dice or AUC number as the contribution.

In our pre-submission reviews of IEEE TMI manuscripts, we flag this when the methodology contribution cannot be stated in one sentence that names a new mechanism, loss, or theoretical result, independent of the dataset it was run on. If your contribution sentence is really "we applied X to Y," IEEE TMI will read it as an application and the desk filter removes it, regardless of clinical interest.

Page-limit non-compliance at the administrative check. A second recurring pattern in the IEEE TMI manuscripts we review is a paper that exceeds the strict 10-page initial-submission limit including references. The administrative screen returns it before any Associate Editor evaluates the science. We repeatedly see strong methods buried under a long related-work section and dense conference-style figures that spend pages on generic deep-learning background.

The fix is to use the introduction and the first method figure to make the medical-imaging contribution visible, and to move generic background into the supplementary material so the methods earn the space.

Non-standardized validation a reviewer cannot trust. Across our IEEE TMI pre-submission reviews, a recurring failure is a central claim resting on a single bespoke dataset with no comparison against current baselines on standardized medical-imaging benchmarks, no cross-validation, and statistical analysis that does not match the design.

IEEE TMI reviewers screen the experimental section closely; a headline number with no ablation isolating where the gain comes from, and no evidence it generalizes beyond one split, reads as an engineering result rather than a methods contribution. Check that every headline claim has a standardized comparison and a statistical test appropriate to your data structure.

Scope drift into informatics, devices, or physics. The fourth pattern is a paper whose true center of gravity is clinical decision support, a biomedical device, or imaging physics, wearing an imaging-methodology label. When the real question belongs to IEEE Journal of Biomedical and Health Informatics, IEEE Transactions on Biomedical Engineering, or Medical Physics, the IEEE TMI desk filter routes it out fast, regardless of quality.

Read your own abstract and ask: is a reusable medical-imaging method the actual protagonist, or a wrapper around a different field's question? If it is a wrapper, the right move is the matching sister journal, not a resubmission.

Don't just blast the same PDF down the ladder. An IEEE TMI rejection that cited a thin methodology delta or weak validation will produce the same outcome at Medical Image Analysis or IEEE Transactions on Image Processing, because those reviewers apply a similar standard and you may even draw the same reviewer pool. The fix is not a formatting pass, and some manuscripts need real work, not a faster next submission.

Be honest about which kind of rejection you got. A desk rejection for scope or for exceeding the strict 10-page limit is a routing-and-reformatting problem you can fix by choosing the right journal and cutting to its template. A post-screen rejection for a missing methodology contribution, non-standardized validation, or thin generalization is a substance problem, and the same concerns reappear at any serious venue.

Two cases call for real work before resubmitting: if reviewers questioned whether there is a method at all, the manuscript needs a contribution a reviewer can name in one sentence; if the validation was challenged, new standardized-benchmark experiments (and sometimes external validation) are the only fix.

Appealing is rarely worth it: a pure-application or page-limit rejection is an editorial judgment, not a factual error, and the appeal queue is slower than a clean resubmission to a better-fit journal.