Definition and research guide
This page combines a MeSH definition, publication statistics and selected research abstracts. It is a starting point for reading the literature, not a medical textbook or a systematic evidence review.
Content available: 4 complete abstracts (698 words), 10 references. Full article text is not stored or reproduced here; follow the PMID, DOI or PMC links to read the original sources and their access terms.
Definition
Reference points located by visual inspection, palpation, or computer assistance, that are useful in localizing structures on or within the human body.
Definition: NLM Medical Subject Headings (MeSH) scope note (Public domain (U.S. National Library of Medicine); attribution requested). View the MeSH record.
Also known as: Anatomic Landmark; Landmark, Anatomic; Landmarks, Anatomic.
Where it fits in the MeSH classification
- Broader topics
- Body Regions
- See also
- Fiducial Markers
Research landscape
PubMed indexes 4,687 records tagged with the MeSH heading “Anatomic Landmarks” (counts retrieved 2026-10-31). 1,424 of them (30.4%) were published from 2020 onward, and the busiest period so far is 2010-2019 with 3,355 records.
Reviews account for 277 records (5.9%) and meta-analyses for 41. Randomized controlled trials number 112 (2.4%) as a share of all records on the topic.
Show the data
| Period | Records |
|---|---|
| through 1999 | 0 |
| 2000-2009 | 3 |
| 2010-2019 | 3,355 |
| 2020 onward | 1,424 |
Publication-type chart data
| Type | Records | Share |
|---|---|---|
| Reviews | 277 | 5.9% |
| Meta-analyses | 41 | 0.9% |
| Randomized controlled trials | 112 | 2.4% |
Method: PubMed query "Anatomic Landmarks"[MeSH Terms] with publication-type and date filters, retrieved 2026-10-31.
Reading the evidence in anatomy and physiology
Anatomy describes how body structures are built and physiology describes how they normally work, so most findings here are descriptive or mechanistic rather than evidence about treatment. Much of what is known comes from dissection, imaging, tissue studies and experiments in animals, and measurements in healthy volunteers can differ from those in people with disease or at different ages. Normal ranges vary between individuals and populations. Check whether a result was measured in people or in another species, the age and health of the participants, and the method used.
Evidence from open-access studies
These open-access studies come from PubMed’s best-match results for this heading (papers whose main topic it is), ranked here by citation count, with one recent addition. Each abstract is reproduced in full under its recorded open licence so that you can read the authors’ own words. They illustrate the literature; they are not a systematic summary of it. Citation counts measure attention, not reliability or clinical benefit.
| Study / authors | Year | Source label / design | Europe PMC citations | Licence / source |
|---|---|---|---|---|
| Mindboggling morphometry of human brains | 2017 | Research article Design not recorded in structured metadata | 682 | cc by PMID 28231282 · DOI · PMC5322885 |
| Universal atrial coordinates applied to visualisation, registration and construction of patient specific meshes | 2019 | Research article Design not recorded in structured metadata | 81 | cc by PMID 31026761 · DOI · PMC6543067 |
| Deep learning approach for automatic landmark detection and alignment analysis in whole-spine lateral radiographs | 2021 | Research article Design not recorded in structured metadata | 67 | cc by PMID 33828159 · DOI · PMC8027006 |
| Validation of an Endoscopic Landmark for Injection of Internal Branch of Superior Laryngeal Nerve | 2026 | Research article Design not recorded in structured metadata | 2 | cc by PMID 40828033 · DOI · PMC12770797 |
Mindboggling morphometry of human brains [1]
Abstract reading summary — source excerpts
- Opening excerpt
- Mindboggle (http://mindboggle.
- Closing excerpt
- All data, code, and results of these evaluations are publicly available.
- Interpretation limits
- Verbatim excerpts from the authors’ abstract; the closing excerpt may describe a finding, limitation or recommendation. Design, population, effect size and uncertainty have not been independently extracted or appraised. Read the complete abstract and linked paper before interpreting the findings.
Read complete abstract (181 words)
Mindboggle (http://mindboggle.info) is an open source brain morphometry platform that takes in preprocessed T1-weighted MRI data and outputs volume, surface, and tabular data containing label, feature, and shape information for further analysis. In this article, we document the software and demonstrate its use in studies of shape variation in healthy and diseased humans. The number of different shape measures and the size of the populations make this the largest and most detailed shape analysis of human brains ever conducted. Brain image morphometry shows great potential for providing much-needed biological markers for diagnosing, tracking, and predicting progression of mental health disorders. Very few software algorithms provide more than measures of volume and cortical thickness, while more subtle shape measures may provide more sensitive and specific biomarkers. Mindboggle computes a variety of (primarily surface-based) shapes: area, volume, thickness, curvature, depth, Laplace-Beltrami spectra, Zernike moments, etc. We evaluate Mindboggle's algorithms using the largest set of manually labeled, publicly available brain images in the world and compare them against state-of-the-art algorithms where they exist. All data, code, and results of these evaluations are publicly available.
Abstract reproduced from the open-access article under the recorded cc by licence; © the authors. PMID 28231282 · DOI · PMC5322885
Universal atrial coordinates applied to visualisation, registration and construction of patient specific meshes [2]
Abstract reading summary — source excerpts
- Opening excerpt
- Integrating spatial information about atrial physiology and anatomy in a single patient from multimodal datasets, as well as generalizing these data across patients, requires a common coordinate system.
- Closing excerpt
- In conclusion, we have developed a universal atrial coordinate system allowing automatic registration of imaging and electroanatomic mapping data, 2D visualisation, and patient specific model creation.
- Interpretation limits
- Verbatim excerpts from the authors’ abstract; the closing excerpt may describe a finding, limitation or recommendation. Design, population, effect size and uncertainty have not been independently extracted or appraised. Read the complete abstract and linked paper before interpreting the findings.
Read complete abstract (222 words)
Integrating spatial information about atrial physiology and anatomy in a single patient from multimodal datasets, as well as generalizing these data across patients, requires a common coordinate system. In the atria, this is challenging due to the complexity and variability of the anatomy. We aimed to develop and validate a Universal Atrial Coordinate (UAC) system for the following applications: combination and assessment of multimodal data; comparison of spatial data across patients; 2D visualization; and construction of patient specific geometries to test mechanistic hypotheses. Left and right atrial LGE-MRI data were segmented and meshed. Two coordinates were calculated for each atrium by solving Laplace's equation, with boundary conditions assigned using five landmark points. The coordinate system was used to map spatial information between atrial meshes, including scalar fields measured using different mapping modalities, and atrial anatomic structures and fibre directions from a reference geometry. Average error in point transfer from a source mesh to a destination mesh and back again was less than 0.1 mm for the left atrium and 0.02 mm for the right atrium. Patient specific meshes were constructed using the coordinate system and phase singularity density maps from arrhythmia simulations were visualised in 2D. In conclusion, we have developed a universal atrial coordinate system allowing automatic registration of imaging and electroanatomic mapping data, 2D visualisation, and patient specific model creation.
Abstract reproduced from the open-access article under the recorded cc by licence; © the authors. PMID 31026761 · DOI · PMC6543067
Deep learning approach for automatic landmark detection and alignment analysis in whole-spine lateral radiographs [3]
Abstract reading summary — source excerpts
- Opening excerpt
- Human spinal balance assessment relies considerably on sagittal radiographic parameter measurement.
- Closing excerpt
- The proposed automatic alignment analysis system was able to localise spinal anatomic landmarks with high accuracy and to generate various radiographic parameters with favourable correlations with manual measurements.
- Interpretation limits
- Verbatim excerpts from the authors’ abstract; the closing excerpt may describe a finding, limitation or recommendation. Design, population, effect size and uncertainty have not been independently extracted or appraised. Read the complete abstract and linked paper before interpreting the findings.
Read complete abstract (171 words)
Human spinal balance assessment relies considerably on sagittal radiographic parameter measurement. Deep learning could be applied for automatic landmark detection and alignment analysis, with mild to moderate standard errors and favourable correlations with manual measurement. In this study, based on 2210 annotated images of various spinal disease aetiologies, we developed deep learning models capable of automatically locating 45 anatomic landmarks and subsequently generating 18 radiographic parameters on a whole-spine lateral radiograph. In the assessment of model performance, the localisation accuracy and learning speed were the highest for landmarks in the cervical area, followed by those in the lumbosacral, thoracic, and femoral areas. All the predicted radiographic parameters were significantly correlated with ground truth values (all p < 0.001). The human and artificial intelligence comparison revealed that the deep learning model was capable of matching the reliability of doctors for 15/18 of the parameters. The proposed automatic alignment analysis system was able to localise spinal anatomic landmarks with high accuracy and to generate various radiographic parameters with favourable correlations with manual measurements.
Abstract reproduced from the open-access article under the recorded cc by licence; © the authors. PMID 33828159 · DOI · PMC8027006
Validation of an Endoscopic Landmark for Injection of Internal Branch of Superior Laryngeal Nerve [4]
Abstract reading summary — source excerpts
- Opening excerpt
- ObjectiveThis study aims to validate a novel transnasal endoscopic approach for accurately targeting the internal branch of the superior laryngeal nerve (iSLN) via the piriform sinus, with the goal of improving treatment outcomes for laryngeal sensory dysfunction (LSD).
- Closing excerpt
- ConclusionThe transnasal approach provides a reliable, anatomically precise method for accessing the iSLN, offering potential advantages over traditional external techniques in the management of LSD.
- Interpretation limits
- Verbatim excerpts from the authors’ abstract; the closing excerpt may describe a finding, limitation or recommendation. Design, population, effect size and uncertainty have not been independently extracted or appraised. Read the complete abstract and linked paper before interpreting the findings.
Read complete abstract (124 words)
ObjectiveThis study aims to validate a novel transnasal endoscopic approach for accurately targeting the internal branch of the superior laryngeal nerve (iSLN) via the piriform sinus, with the goal of improving treatment outcomes for laryngeal sensory dysfunction (LSD).MethodsEight cadaveric larynges were examined using a 3D-printed cadaveric laryngeal model. The superolateral quadrant of the piriform sinus was endoscopically marked with toluidine blue ink. The distance between the ink mark and the iSLN confluence point was measured as well as other landmarks.ResultsThe mean distance from the ink to the iSLN confluence was 5.38 mm, with significantly less variability than traditional external landmarks.ConclusionThe transnasal approach provides a reliable, anatomically precise method for accessing the iSLN, offering potential advantages over traditional external techniques in the management of LSD.
Abstract reproduced from the open-access article under the recorded cc by licence; © the authors. PMID 40828033 · DOI · PMC12770797
Key reviews and meta-analyses
The most cited review-type papers among PubMed’s best-match results for this heading, listed with bibliographic details only. Follow the links for the full text and access terms.
- Research article Proposed lexicon for anatomic landmarks in normal posterior segment spectral-domain optical coherence tomography: the IN•OCT consensus [5]
- Research article Ultrasound guidance versus anatomical landmarks for internal jugular vein catheterization [6]
- Research article Ultrasound guidance versus anatomical landmarks for subclavian or femoral vein catheterization [7]
- Research article The subject-fixated coaxially sighted corneal light reflex: a clinical marker for centration of refractive treatments and devices [8]
- Research article Utility of fluorescent cholangiography during laparoscopic cholecystectomy: A systematic review [9]
- Research article Fetal imaging: executive summary of a joint Eunice Kennedy Shriver National Institute of Child Health and Human Development, Society for Maternal-Fetal Medicine, American Institute of Ultrasound in Medicine, American College of Obstetricians and Gynecologists, American College of Radiology, Society for Pediatric Radiology, and Society of Radiologists in Ultrasound Fetal Imaging Workshop [10]
References
- Klein A, Ghosh SS, Bao FS, Giard J, Häme Y, Stavsky E, et al.. Mindboggling morphometry of human brains. . 2017. PMID 28231282 · DOI · PMC5322885
- Roney CH, Pashaei A, Meo M, Dubois R, Boyle PM, Trayanova NA, et al.. Universal atrial coordinates applied to visualisation, registration and construction of patient specific meshes. . 2019. PMID 31026761 · DOI · PMC6543067
- Yeh YC, Weng CH, Huang YJ, Fu CJ, Tsai TT, Yeh CY. Deep learning approach for automatic landmark detection and alignment analysis in whole-spine lateral radiographs. . 2021. PMID 33828159 · DOI · PMC8027006
- Tanigami Y, Hortobagyi D, Bowen AJ, Kruse C, Dailey SH. Validation of an Endoscopic Landmark for Injection of Internal Branch of Superior Laryngeal Nerve. . 2026. PMID 40828033 · DOI · PMC12770797
- Staurenghi G, Sadda S, Chakravarthy U, Spaide RF, International Nomenclature for Optical Coherence Tomography (IN•OCT) Panel. Proposed lexicon for anatomic landmarks in normal posterior segment spectral-domain optical coherence tomography: the IN•OCT consensus. Ophthalmology. 2014. PMID 24755005 · DOI
- Brass P, Hellmich M, Kolodziej L, Schick G, Smith AF. Ultrasound guidance versus anatomical landmarks for internal jugular vein catheterization. Cochrane Database Syst Rev. 2015. PMID 25575244 · DOI · PMC6517109
- Brass P, Hellmich M, Kolodziej L, Schick G, Smith AF. Ultrasound guidance versus anatomical landmarks for subclavian or femoral vein catheterization. Cochrane Database Syst Rev. 2015. PMID 25575245 · DOI · PMC6516998
- Chang DH, Waring GO. The subject-fixated coaxially sighted corneal light reflex: a clinical marker for centration of refractive treatments and devices. Am J Ophthalmol. 2014. PMID 25127696 · DOI
- Pesce A, Piccolo G, La Greca G, Puleo S. Utility of fluorescent cholangiography during laparoscopic cholecystectomy: A systematic review. World J Gastroenterol. 2015. PMID 26167088 · DOI · PMC4491975
- Reddy UM, Abuhamad AZ, Levine D, Saade GR, Fetal Imaging Workshop Invited Participants. Fetal imaging: executive summary of a joint Eunice Kennedy Shriver National Institute of Child Health and Human Development, Society for Maternal-Fetal Medicine, American Institute of Ultrasound in Medicine, American College of Obstetricians and Gynecologists, American College of Radiology, Society for Pediatric Radiology, and Society of Radiologists in Ultrasound Fetal Imaging Workshop. J Ultrasound Med. 2014. PMID 24764329 · DOI
About this article
- Sources
- NLM Medical Subject Headings (definition, synonyms); NCBI PubMed (counts, identifiers); Europe PMC (open-access abstracts and citation counts).
- Verification
- Every reference was resolved against PubMed on 2026-10-31; title, year and DOI matched.
- Review state
- automated source verified; no human expert review has been recorded yet.
- Version
- 1, last updated 2026-10-31.
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Evidence strength
EvidenceHelix's computed view of the study designs behind this topic: how common meta-analyses, randomized trials and reviews are, how recent the literature is, and a plain-language reading. It describes the design mix of the literature. It is not a quality appraisal of any study, and it is not medical advice.