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Here, we present and evaluate automated methods of frontal lobe parcellation with the programs FreeSurfer(FS) and TOADS\u2010CRUISE(T\u2010C), based on the manual method described in Ranta et al. [2009]: Psychiatry Res 172:147\u2010154 in which sulcal\u2010gyral landmarks were used to manually delimit functionally relevant regions within the frontal lobe: i.e., primary motor cortex, anterior cingulate, deep white matter, premotor cortex regions (supplementary motor complex, frontal eye field, and lateral premotor cortex) and prefrontal cortex (PFC) regions (medial PFC, dorsolateral PFC, inferior PFC, lateral orbitofrontal cortex [OFC] and medial OFC). Dice's coefficient, a measure of overlap, and percent volume difference were used to measure the reliability between manual and automated delineations for each frontal lobe region. For FS, mean Dice's coefficient for all regions was 0.75 and percent volume difference was 21.2%. For T\u2010C the mean Dice's coefficient was 0.77 and the mean percent volume difference for all regions was 20.2%. These results, along with a high degree of agreement between the two automated methods (mean Dice's coefficient = 0.81, percent volume difference = 12.4%) and a proof\u2010of\u2010principle group difference analysis that highlights the consistency and sensitivity of the automated methods, indicate that the automated methods are valid techniques for parcellation of the frontal lobe into functionally relevant sub\u2010regions. Thus, the methodology has the potential to increase efficiency, statistical power and reproducibility for population analyses of neuropsychiatric disorders with hypothesized frontal lobe contributions. <jats:italic>Hum Brain Mapp 35:2009\u20132026, 2014<\/jats:italic>. \u00a9 <jats:bold>2013 Wiley Periodicals, Inc<\/jats:bold>.<\/jats:p>","DOI":"10.1002\/hbm.22309","type":"journal-article","created":{"date-parts":[[2013,7,29]],"date-time":"2013-07-29T13:02:59Z","timestamp":1375102979000},"page":"2009-2026","source":"Crossref","is-referenced-by-count":26,"title":["Automated MRI parcellation of the frontal lobe"],"prefix":"10.1002","volume":"35","author":[{"given":"Marin E.","family":"Ranta","sequence":"first","affiliation":[{"name":"Kennedy Krieger Institute Laboratory for Neurocognitive Imaging and Research Baltimore Maryland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Min","family":"Chen","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Engineering Johns Hopkins University Baltimore Maryland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Deana","family":"Crocetti","sequence":"additional","affiliation":[{"name":"Kennedy Krieger Institute Laboratory for Neurocognitive Imaging and Research Baltimore Maryland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jerry L.","family":"Prince","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Engineering Johns Hopkins University Baltimore Maryland"},{"name":"Department of Radiology and Radiological Science Johns Hopkins University Baltimore Maryland"},{"name":"Department of Biomedical Engineering Johns Hopkins University Baltimore Maryland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Krish","family":"Subramaniam","sequence":"additional","affiliation":[{"name":"Athinoula A. 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