The anterior portion of the medial temporal lobe (MTL) is one of the first regions targeted by pathology in sporadic Alzheimer's disease (AD) and limbic-predominant age-related TDP-43 encephalopathy (LATE) indicating a potential for metrics from this region to serve as imaging biomarkers. Leveraging a unique post-mortem dataset of histology and magnetic resonance imaging (MRI) scans, we aimed to (1) develop an anatomically valid segmentation protocol for anterior entorhinal cortex (ERC), Brodmann area (BA) 35, and BA36 for in vivo 3 T MRI and (2) incorporate this protocol in an automated approach. We included 20 cases (61-97 years old, 50% females) with and without neurodegenerative diseases (11 vs. 9 cases) to ensure generalizability of the developed protocol. Digitized MTL Nissl-stained coronal histology sections from these cases were annotated and registered to same-subject post-mortem MRI. The protocol was developed by determining the location of histological borders of the MTL cortices in relation to anatomical landmarks. Subsequently, the protocol was applied to 15 cases twice, with a 2-week interval, to assess intra-rater reliability with the Dice Similarity Index (DSI). Thereafter, it was implemented in our in-house Automatic Segmentation of Hippocampal Subfields (ASHS)-T1 approach and evaluated with DSIs. The anterior histological border distances of ERC, BA35 and BA36 were evaluated with respect to various anatomical landmarks, and the distance relative to the beginning of the hippocampus was chosen. To formulate segmentation rules, we examined the histological sections for the location of borders in relationship to anatomical landmarks in the coronal sections. The DSI for the anterior MTL cortices for the intra-rater reliability was 0.85-0.88, and for the ASHS-T1 against the manual segmentation, it was 0.62-0.65. We developed a reliable segmentation protocol and incorporated it in an automated approach. Given the vulnerability of the anterior MTL cortices to tau deposition in AD and LATE, the updated approach is expected to improve imaging biomarkers for these diseases.