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Building a smart system for grading pimple scars

Developing Machine Learning Models for Classification and Severity Grading of Atrophic Acne Scar Types from Face Images - NIL

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
CTRI
Registry ID
CTRI/2025/04/084209
Enrollment
223
Registered
2025-04-07
Start date
Unknown
Completion date
Unknown
Last updated
2025-04-28

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Health Condition 1: L905- Scar conditions and fibrosis of skin

Interventions

Intervention1: NIL: NIL Control Intervention1: NIL: NIL

Sponsors

Joiesmary D Souza
Lead Sponsor
Dr Venkatesh Bhandage
Collaborator

Eligibility

Inclusion criteria

Inclusion criteria: Patients who have atrophic acne scar on face

Exclusion criteria

Exclusion criteria: 1. Patients with Keloid and Hypertrophic scar 2. Acne scar on areas other than face

Design outcomes

Primary

MeasureTime frame
Develop an automated deep learning-based system for classifying acne scars into the 3 classes Developing an Acne Scar severity detection system.Timepoint: 3 years—

Secondary

MeasureTime frame
Develop a dataset of acne scar images labeled into 3 different classes and validating by experienced dermatologistsTimepoint: 3 years—

Countries

India

Contacts

Public ContactDr Venkatesh Bhandage

Manipal Institute of Technology, Manipal

venkatesh.bhandage@manipal.edu9916262655

Outcome results

None listed

Source: CTRI (via WHO ICTRP) · Data processed: Feb 4, 2026