A Multi-Parameter Corneal Tomography Dataset for Machine Learning–Driven IOL Selection and Corneal Subtype Classification

Description

This dataset contains Pentacam-derived corneal tomographic and biometric parameters collected from 61 eyes of patients undergoing preoperative assessment for cataract surgery with intraocular lens (IOL) implantation. The data were acquired using a standardized Scheimpflug tomography protocol with the Pentacam HR system. Each record represents a single eye and includes 35 variables encompassing anterior and posterior corneal curvature (K1, K2, KMAX), astigmatism magnitude and axis, corneal asphericity (Q-value), Total Corneal Refractive Power (TCRP), higher-order aberrations (HOA), spherical aberration (Z4,0), the Belin/Ambrósio Deviation index (BAD-D), wavefront root-mean-square (RMS) metrics, central corneal thickness (CCT), anterior chamber parameters, white-to-white distance (HWTW), corneal volume, axial length, refractive error classification, pupil diameter, and selected IOL type. Eyes are clinically classified into six corneal subtypes: Normal High spherical aberration Fuchs endothelial corneal dystrophy High higher-order aberrations Combined high HOA and high SA High HOA with corneal ectasia The dataset is provided as a structured Excel file (.xlsx) with one row per eye and one column per parameter. A companion parameter glossary document (.docx) defines all variables, units, and normative reference ranges.

Institutions

• Daffodil International University

  Dhaka Division, Dhaka

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