title: Abnormal red blood cells detection using adaptive neuro-fuzzy system.
abstract: Features like size, shape, and volume of red blood cells are important factors in diagnosing related blood disorders such as iron deficiency and anemia. This paper proposes a method to detect abnormality in red blood cells using cell microscopic images. Adaptive local thresholding and bounding box methods are used to extract inner and outer diameters of red cells. An adaptive network-based fuzzy inference system (ANFIS) is used to classify blood samples to normal and abnormal. Accuracy of the proposed method and area under ROC curve are 96.6% and 0.9950 respectively.
authors.affiliation: Department of Artificial Intelligence, Science and Research Branch, Islamic Azad University, Tehran, Iran.
authors.forename: Nahid
authors.initials: N
authors.lastname: Babazadeh Khameneh
authors.forename: Hossein
authors.initials: H
authors.lastname: Arabalibeik
authors.forename: Piruz
authors.initials: P
authors.lastname: Salehian
authors.forename: Saeed
authors.initials: S
authors.lastname: Setayeshi
mesh_terms: D003936:Diagnosis, Computer-Assisted; D004913:Erythrocytes, Abnormal / Q000502:physiology*; D017143:Fuzzy Logic; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods; D008853:Microscopy; D016571:Neural Networks, Computer