76 Int. J. Biomedical Engineering and Technology, Vol. 27, Nos. 1/2, 2018 Copyright © 2018 Inderscience Enterprises Ltd. Regenerative pixel mode and tumour locus algorithm development for brain tumour analysis: a new computational technique for precise medical imaging Sunil L. Bangare* Department of Computer Science & Engineering, Koneru Lakshmaiah Education Foundation (K.L.E.F.), Guntur, Andhra Pradesh, India and Department of IT, Sinhgad Academy of Engineering, Pune, India Email: sunil.bangare@gmail.com *Corresponding author G. Pradeepini Department of Computer Science & Engineering, Koneru Lakshmaiah Education Foundation (K.L.E.F.), Guntur, Andhra Pradesh, India Email: pradeepini_cse@kluniversity.in Shrishailappa T. Patil Department of Computer Engineering, Vishwakarma Institute of Technology, Pune, India Email: stpatil77@gmail.com Abstract: This paper provides Regenerative Pixel Mode (RPM) and Tumour Locus algorithm (TLA), an alternative technique for effective anti-aliased extraction of complicated tumour locus. We developed this technology to eliminate disadvantages of Positron Emission Tomography (PET) scan technology where radioactive material proved as a risk for the patient. The presented technology can be an alternative to PET scan processes and is very cost-effective technique as compared to PET scan. RPM algorithm makes use of the pixel sampling, sub-pixel filter mode to build a compressed, tumour manifestation in each and every pixel through the elimination of impurities. Along with RPM algorithm, TLA is further used for identification of tumour locus by a sub-clustering method where the high-intensity region of the brain tumour is extracted. Finally, RPM and TLA processing provide final results which are undoubtedly visible for health practitioner reviews for pre and post or even during surgical activities. Keywords: RPM; regenerative pixel mode; TLA; tumour locus algorithm; MRI; magnetic resonance image; PET; positron emission tomography; brain tumour; clustering; Groebner bases.