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Anusha Achuthan - IEEE Xplore Author Profile
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Anusha Achuthan

Publications
7
Citations
21
Publications by Year
20062024
Co-Authors:
Show All Co-Authors (18)
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Anusha Achuthan

Affiliation

School of Computer Sciences
Universiti Sains Malaysia
Gelugor, Malaysia

Publication Topics

Biography

Anusha Achuthan (Member, IEEE) received the Ph.D. degree specializing in computer vision and medical image analysis from Universiti Sains Malaysia, in 2016. She is currently a Senior Lecturer at the School of Computer Sciences, Universiti Sains Malaysia. Her research interests include the areas of computational neuroscience, knowledge guided image analysis, biomarkers analysis for neurological disorders and aging, machine learning, and computer vision. She is a member of ISMRM and IACSIT. Besides research work, she is also very passionate about online teaching and learning resources. She has developed a MOOC course on scientific writing and delivered workshops on e-learning modules.(Based on document published on 14 October 2022).
Publications
7
Citations
21
Publications by Year
20062024
Co-Authors:
Show All Co-Authors (18)
Author's Published Works

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State-of-the-Art and Challenges in Pancreatic CT Segmentation: A Systematic Review of U-Net and Its Variants

Chaohui Zhang;Anusha Achuthan;Galib Muhammad Shahriar Himel

IEEE Access
Year: 2024 | Volume: 12 | Journal Article |
Cited by: Papers (1)
In medical image analysis, segmenting pancreatic CT images presents a significant challenge due to the complex anatomy of the pancreas and the generally low contrast of these images. Accurate pancreas segmentation is crucial in clinical scenarios, particularly for the diagnosis and treatment of pancreatic cancer. The U-Net architecture and its variations have achieved significant progress in deep ...Show More

State-of-the-Art and Challenges in Pancreatic CT Segmentation: A Systematic Review of U-Net and Its Variants

Chaohui Zhang;Anusha Achuthan;Galib Muhammad Shahriar Himel

Year: 2024 | Volume: 12 | Journal Article |

Conceptual Framework For Optimized Pipeline Selection For Brain Tractography Using Multi-Criteria Decision Analysis

Idrees Fazili;Anusha Achuthan;Muzaimi Mustapha;Bahari Belaton

2022 7th International Conference on Communication, Image and Signal Processing (CCISP)
Year: 2022 | Conference Paper |
Diffusion Tensor Imaging (DTI) allows us to reconstruct the brain white matter (WM) pathways in-vivo. Generating a diffusion tractograph from raw MRI data involves multiple layers of processes. Each set of processes that produces a particular analysis is called a pipeline. An extensive collection of software tools have been developed over the years for each layer of tractograph generation, giving ...Show More

Conceptual Framework For Optimized Pipeline Selection For Brain Tractography Using Multi-Criteria Decision Analysis

Idrees Fazili;Anusha Achuthan;Muzaimi Mustapha;Bahari Belaton

Year: 2022 | Conference Paper |

Brain Vessel Segmentation Using Deep Learning—A Review

Mohammad Raihan Goni;Nur Intan Raihana Ruhaiyem;Muzaimi Mustapha;Anusha Achuthan;Che Mohd Nasril Che Mohd Nassir

IEEE Access
Year: 2022 | Volume: 10 | Journal Article |
Cited by: Papers (16)
This article provides a comprehensive review of deep learning-based blood vessel segmentation of the brain. Cerebrovascular disease develops when blood arteries in the brain are compromised, resulting in severe brain injuries such as ischemic stroke, brain hemorrhages, and many more. Early detection enables patients to obtain more effective treatment before becoming critically unwell. Due to the s...Show More

Brain Vessel Segmentation Using Deep Learning—A Review

Mohammad Raihan Goni;Nur Intan Raihana Ruhaiyem;Muzaimi Mustapha;Anusha Achuthan;Che Mohd Nasril Che Mohd Nassir

Year: 2022 | Volume: 10 | Journal Article |

Adaptive Clip Limit Tile Size Histogram Equalization for Non-Homogenized Intensity Images

Ali Fawzi;Anusha Achuthan;Bahari Belaton

IEEE Access
Year: 2021 | Volume: 9 | Journal Article |
Cited by: Papers (2)
Intensity inhomogeneity, hidden details, poor image contrast due to low capturing device quality, limited user experience, and inappropriate environment setting during data acquisition are major issues reported during the image enhancement process. Histogram Equalization (HE) approaches have been commonly deployed to overcome the above-listed problems, apart from improving image contrast. Neverthe...Show More

Adaptive Clip Limit Tile Size Histogram Equalization for Non-Homogenized Intensity Images

Ali Fawzi;Anusha Achuthan;Bahari Belaton

Year: 2021 | Volume: 9 | Journal Article |

Evaluation of Two Sinogram Interpolation Methods for Metal Artefacts Reduction in Computed Tomography

Noor Diyana Osman;Nurul Fathin Mohamad Sobri;Anusha Achuthan;Halimatul Asma Saidun;Mohd Zahri Abdul Aziz;Ibrahim Lutfi Shuaib

2018 IEEE-EMBS Conference on Biomedical Engineering and Sciences (IECBES)
Year: 2018 | Conference Paper |
Cited by: Papers (1)
In the presence of metal implant, it can induce streak artefacts appearance in computed tomography (CT) images that can degrade image quality and lead to misdiagnosis. A comparative study of two different sinogram interpolation methods for metal artefact reduction in CT images is presented. The metal part of the sinogram was determined and removed by thresholding technique. The missing part of the...Show More

Evaluation of Two Sinogram Interpolation Methods for Metal Artefacts Reduction in Computed Tomography

Noor Diyana Osman;Nurul Fathin Mohamad Sobri;Anusha Achuthan;Halimatul Asma Saidun;Mohd Zahri Abdul Aziz;Ibrahim Lutfi Shuaib

Year: 2018 | Conference Paper |

Wavelet Energy Guided Level Set for Segmenting Highly Similar Regions in Medical Images

Anusha Achuthan;Mandava Rajeswari;Dhanesh Ramachandram;Mohd Ezane Aziz;Ibrahim Lutfi

2009 2nd International Conference on Biomedical Engineering and Informatics
Year: 2009 | Conference Paper |
Cited by: Papers (1)
This paper presents a new segmentation method that integrates a wavelet based feature, which is able to enhance the dissimilarity between regions with low variations in intensity. This feature is integrated to formulate a new level set based active contour model that addresses the segmentation of regions with highly similar intensities in medical images, which do not have clear boundaries between ...Show More

Wavelet Energy Guided Level Set for Segmenting Highly Similar Regions in Medical Images

Anusha Achuthan;Mandava Rajeswari;Dhanesh Ramachandram;Mohd Ezane Aziz;Ibrahim Lutfi

Year: 2009 | Conference Paper |

Detection of Secondary Structure in Medical Images using Wavelet and Watershed

Anusha Achuthan;Mandava Rajeswari;Dhanesh Ramachandram

The 2nd International Conference on Distributed Frameworks for Multimedia Applications
Year: 2006 | Conference Paper |
Image segmentation is the most essential and crucial process in order to facilitate the delineation, characterization and visualization of structures of interests in medical images. In recent years, various methods of medical image segmentation have been employed depending on the type of tissues, anatomy of object of interest and imaging modality being used. In this paper, a novel problem specific...Show More

Detection of Secondary Structure in Medical Images using Wavelet and Watershed

Anusha Achuthan;Mandava Rajeswari;Dhanesh Ramachandram

Year: 2006 | Conference Paper |

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