Kernel Metadata Declaration — on demand

ISO 26324 asks a DOI Registration Agency to produce a Kernel Metadata Declaration for every DOI it issues. Give any DOI: its public record becomes a record in the Smart Scholars DOI Metadata Format 1.0, checked against every rule, and declared as the Kernel XML.

✓ Meets every rule of the format

The record below is complete and every controlled value is a DOI Attribute Value Set 2.3 spelling. The Declaration on the right follows DOIMetadataKernel.xsd element by element.

What the DOI identifies

BRAIN TUMOR DETECTION FROM MRI IMAGE USING DIGITAL IMAGE PROCESSING

10.46243/jst.2023.v8.i06.pp95-100 · JournalArticle — an article in a journal · Digital · Visual · Language · en

Published 2023-08-07

Part of Journal of Science & Technology · ISSN 2456-5660 · vol. 8 · no. 7 · pp. 95–100

Principal agents

H BHAGYA LAKSHMI H BHAGYA LAKSHMI (author → Author)
Longman Publishers (publisher → Publisher)

Also in the record, outside the Kernel: the abstract, the licence, 3 links, 0 references. Source: Crossref (member 25296), registered 2024-02-16, last deposited 2026-09-28.

⬇ Record (JSON) ⬇ Declaration (XML)

System metadata — ISO 26324:2025, Annex B · DOI Handbook 10.1

Each element by the standard's name and the Handbook's (in grey), read off the record.

DOI Name DOI name	10.46243/jst.2023.v8.i06.pp95-100
Referent Type referentType	Creation
Referent Sub-Type referentSubType	JournalArticle — an article in a journal
Referent Name(s) referentName(s)	BRAIN TUMOR DETECTION FROM MRI IMAGE USING DIGITAL IMAGE PROCESSING (PrincipalTitle, en)
Basic Metadata basicMetadata	author: H BHAGYA LAKSHMI H BHAGYA LAKSHMI publisher: Longman Publishers published: 2023-08-07 part of: Journal of Science & Technology · ISSN 2456-5660 · vol. 8 · no. 7 · pp. 95–100 language: en form: Digital · Visual · Language
Referent Identifier(s) alternateIdentifier(s)	none besides the DOI
Registration Authority registrationAuthorityCode	Crossref — issued by Crossref (member 25296); held here as a copy
Created Date issueDate	2024-02-16
relatedIdentifiers	none needed — the descriptive metadata is in this record

The record

{
    "format": "smartscholars-doi-metadata/1.0",
    "doi": "10.46243/jst.2023.v8.i06.pp95-100",
    "referent": "Creation",
    "type": "JournalArticle",
    "structural_type": "Digital",
    "modes": [
        "Visual"
    ],
    "characters": [
        "Language"
    ],
    "titles": [
        {
            "value": "BRAIN TUMOR DETECTION FROM MRI IMAGE USING DIGITAL IMAGE PROCESSING",
            "type": "PrincipalTitle",
            "lang": "en"
        }
    ],
    "identifiers": [
        {
            "type": "DOI",
            "value": "10.46243/jst.2023.v8.i06.pp95-100"
        }
    ],
    "agents": [
        {
            "role": "author",
            "name": {
                "given": "H BHAGYA LAKSHMI",
                "family": "H BHAGYA LAKSHMI"
            },
            "sequence": "first"
        },
        {
            "role": "publisher",
            "name": {
                "org": "Longman Publishers"
            }
        }
    ],
    "dates": {
        "published": "2023-08-07",
        "date_type": "PublicationDate",
        "online": "2023-08-07"
    },
    "language": "en",
    "container": {
        "type": "Journal",
        "titles": [
            {
                "value": "Journal of Science & Technology",
                "type": "PrincipalTitle"
            }
        ],
        "identifiers": [
            {
                "type": "ISSN",
                "value": "2456-5660",
                "medium": "electronic"
            }
        ],
        "volume": "8",
        "issue": "7",
        "pages": {
            "first": "95",
            "last": "100"
        }
    },
    "links": [
        {
            "url": "https://www.jst.org.in/index.php/pub/article/view/716",
            "return_type": "text/html",
            "primary": true
        },
        {
            "url": "https://www.jst.org.in/index.php/pub/article/download/716/647",
            "purpose": "text-mining",
            "return_type": "application/pdf"
        },
        {
            "url": "https://www.jst.org.in/index.php/pub/article/download/716/2372",
            "purpose": "text-mining",
            "return_type": "application/xml"
        }
    ],
    "abstract": {
        "value": "Brain tumor is the main threat among the people. But currently, it become more advanced because of the many Machine Learning techniques. Magnetic Resonance Imaging is the greatest technique among all the image processing techniques which scans the human body and gives a clear resolution of the tumors in an improved quality image. The fundamentals of MRI are to develop images based on magnetic field and radio waves of the anatomy of the body. The major area of segmentation of images is medical image processing. Better results are provided by MRI images than CT scan, Xrays etc. Nowadays the automatic tumor detection in large spatial and structural variability. Recently Convolutional Neural Network plays an important role in medical field and computer vision. One of its application is the identification of brain tumor. Here, the pre-processing technique is used to convert normal images to grayscale values because it contains equal intensity but in MRI, RGB content is included. Then filtering is used to remove the unwanted noises using median and high pass filter for better quality of images. The deeper architecture design in CNN is performed using small kernels. Finally, the effect of using this network for segmentation of tumor from MRI images is evaluated with better results.",
        "lang": "en"
    },
    "license": {
        "url": "https://creativecommons.org/licenses/by/4.0",
        "start": "2023-08-07",
        "applies_to": "vor"
    },
    "record": {
        "registrant": "Longman Publishers",
        "registered": "2024-02-16",
        "updated": "2026-09-28",
        "issue_number": 1,
        "source": "crossref-api",
        "source_agency": "Crossref (member 25296)"
    }
}

The Kernel Metadata Declaration

DOIMetadataKernel.xsd · namespace http://www.doi.org/2010/DOISchema · Attribute Value Sets 2.3 · draft — the agency's DOI name is filled in on accreditation

<?xml version="1.0" encoding="UTF-8"?>
<!-- DRAFT declaration: Smart Scholars is not yet a DOI Registration Agency. registrationAgencyDoiName is a marker (10.0/ is no RA's prefix) and is filled in on accreditation. -->
<kernelMetadata xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.doi.org/2010/DOISchema https://www.doi.org/doi_schemas/DOIMetadataKernel.xsd" xmlns="http://www.doi.org/2010/DOISchema">
  <referentDoiName>10.46243/jst.2023.v8.i06.pp95-100</referentDoiName>
  <primaryReferentType>Creation</primaryReferentType>
  <registrationAgencyDoiName>10.0/smart-scholars-draft</registrationAgencyDoiName>
  <issueDate>2026-10-04</issueDate>
  <issueNumber>1</issueNumber>
  <referentCreation>
    <name primaryLanguage="en">
      <value>BRAIN TUMOR DETECTION FROM MRI IMAGE USING DIGITAL IMAGE PROCESSING</value>
      <type>PrincipalTitle</type>
    </name>
    <identifier>
      <nonUriValue>10.46243/jst.2023.v8.i06.pp95-100</nonUriValue>
      <uri returnType="text/html" doesContentNegotiation="true">https://doi.org/10.46243/jst.2023.v8.i06.pp95-100</uri>
      <type>DOI</type>
    </identifier>
    <identifier>
      <uri returnType="text/html">https://www.jst.org.in/index.php/pub/article/view/716</uri>
      <type>URI</type>
    </identifier>
    <identifier>
      <uri>https://www.jst.org.in/index.php/pub/article/download/716/647</uri>
      <type>URI</type>
    </identifier>
    <identifier>
      <uri returnType="application/xml">https://www.jst.org.in/index.php/pub/article/download/716/2372</uri>
      <type>URI</type>
    </identifier>
    <structuralType>Digital</structuralType>
    <mode>Visual</mode>
    <character>Language</character>
    <type>JournalArticle</type>
    <principalAgent>
      <name>
        <value>H BHAGYA LAKSHMI H BHAGYA LAKSHMI</value>
        <type>PrincipalName</type>
      </name>
      <role>Author</role>
    </principalAgent>
    <principalAgent>
      <name>
        <value>Longman Publishers</value>
        <type>PrincipalName</type>
      </name>
      <role>Publisher</role>
    </principalAgent>
    <linkedCreation>
      <name>
        <value>Journal of Science &amp; Technology</value>
        <type>PrincipalTitle</type>
      </name>
      <identifier>
        <nonUriValue>2456-5660</nonUriValue>
        <type>ISSN</type>
      </identifier>
      <referentCreationRole>Part</referentCreationRole>
      <referentCreationSequenceIdentifier>
        <value>8</value>
        <type>VolumeNumber</type>
      </referentCreationSequenceIdentifier>
      <referentCreationSequenceIdentifier>
        <value>7</value>
        <type>IssueNumber</type>
      </referentCreationSequenceIdentifier>
      <referentCreationSequenceIdentifier>
        <value>95-100</value>
        <type>PageNumber</type>
      </referentCreationSequenceIdentifier>
    </linkedCreation>
    <language>en</language>
    <languageOfReferentContent>
      <language>en</language>
      <languageOfReferentContentType>Original</languageOfReferentContentType>
    </languageOfReferentContent>
    <creationDate>
      <date>2023-08-07</date>
      <creationDateType>PublicationDate</creationDateType>
    </creationDate>
  </referentCreation>
</kernelMetadata>

Kernel Metadata Declaration — on demand

✓ Meets every rule of the format

What the DOI identifies

System metadata — ISO 26324:2025, Annex B · DOI Handbook 10.1

The record

The Kernel Metadata Declaration

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