Early detection and treatment of high-grade dysplasia (HGD) in Barrett's esophagus may reduce the risk of developing esophageal adenocarcinoma. Confocal endomicroscopy (CLE) has shown advantages over routine white-light endoscopic surveillance with biopsy for histological examination; however, CLE is compromised by insufficient contrast and by intra- and interobserver variation. An FDA-approved PDT photosensitizer was used here to reveal morphological and textural features similar to those found in histological analysis. Support vector machines were trained using the aforementioned features to obtain an automatic and robust detection of HGD. Our results showed 95% sensitivity and 87% specificity using the optimal feature combination and demonstrated the potential for extension to a three-dimensional cell model.