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by IQAC KIITKIIT Deemed to be University — Internal Quality Assurance Cell

Publication2019

Deep learning based liver cancer detection using watershed transform and Gaussian mixture model techniques

The record

Type
Publication
Date
1 May 2019
Level
International — held abroad
Journal
Cognitive Systems Research
Volume
54
Pages
165-175
Published
1 May 2019
DOI
10.1016/j.cogsys.2018.12.009
Scopus ID
85059331650
ISSN
13890417
Authors
4
Open access
No
Citations
188
International co-authorship
Yes
Co-author countries
IN, MY, SG

Classification

Every label below carries the reasoning it was assigned on, the confidence band it was assigned in, and what produced it. The rubric is published.

UN Sustainable Development Goals

  1. 3 Ensure healthy lives and promote well-being for all at all ages

    GoalPrimaryCertain confidenceJudged

    Watershed and Gaussian mixture model deep learning achieves 99.38% accuracy in classifying liver cancer types from CT imaging.

    Certain confidence
    The record states the subject matter explicitly. A reader shown only the title and this goal would agree without hesitation. Example: a workshop titled "Renewable Energy and Smart Grid" against SDG 7.
    Judged
    Judged against the published classification rubric, under the rubric and prompt versions recorded with the run that produced it.
    Produced by
    claude-haiku-4-5-20251001, under kortex-publication-v1

  2. 17.6 Enhance North-South, South-South and triangular cooperation on science, technology and innovation, and knowledge sharing

    TargetSecondaryHigh confidenceRule-derivedrule sdg17-structural-v1

    Structural signal: co-authorship outside India.

    High confidence
    The subject matter is a strong and direct inference from the record type, the funding or organising body, or the programme context, even where the title alone is thin. Example: an ICMR-funded project against SDG 3, on the strength of the agency.
    Rule-derived
    Emitted by a deterministic rule from structural signals rather than judged from the record’s text. The rule carries a version, so rule-derived and judged labels stay separable.
    Produced by
    sdg17-structural-v1, under kortex-publication-v1

Viksit Bharat @2047

  1. vb-3.2 Digital technology and artificial intelligence

    Sub-themePrimaryCertain confidenceJudged

    Automated CAD system using DNN classifier enables rapid and accurate liver cancer detection and classification.

    Produced by
    claude-haiku-4-5-20251001, under kortex-publication-v1

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KIIT Deemed to be University. “Deep learning based liver cancer detection using watershed transform and Gaussian mixture model techniques”. Kortex.

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