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Parabolic equation models discretised with the finite‐difference method have been a research topic for a long time. Through the simulation of electromagnetic wave propagation characteristics in typical scenarios, it is pointed out that the fast algorithm needs to be developed for the solution of two‐level Noye–Hayman (NH2) implicit method to meet the accuracy and computational requirements of electromagnetic wave propagation problems in three‐dimensional environments. In this Letter, hierarchical skeletonisation is used for an efficient inversion of three‐dimensional parabolic equation discretised by the NH2 implicit method which is the modification of conventional Crank–Nicolson (CN) method. Numerical results show that the NH2 implicit method is more accurate than the CN method at no additional cost for a given numerical example.

The rapid development of digital imaging and computer vision has extended the potential of using these technologies in the diagnosis of human diseases. Medical image analysis is a non-invasive way to identify human diseases which are usually manually marked by medical experts or automatically detected by the Computer-Aided Diagnostic (CAD) system. The fundus images provide facts and information about visual disorders (diabetic retinopathy, glaucoma, age-related macular degeneration, etc.), brain disease (Alzheimer's), and heart-related diseases (cardiovascular, hypertension, and stroke). Extensive research has been done in the last two decades in developing automated methods for the identification of various human disorders from fundus images. This survey paper provides the reader with a broad review of the fundus image processing for the identification of various human disorders. In this paper, human diseases that can be diagnosed through fundus images are reviewed. Several publicly available fundus datasets which are helpful in the screening of these abnormalities are briefly discussed. This work aims to show the importance of retinal images in the diagnosis of different human diseases. The main challenges and difficulties faced in effective diagnosis are presented and discussed. We believe that this work will guide the researchers in addressing the challenges in existing solutions and assist doctors in the proper diagnosis of various diseases.

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