8 May 2023 Contributions of global and local processing on medical image perception
Hyung-Bum Park, Lilian Azer, Shinhae Ahn, Tam-Dan Dinh, Gabriela Macias, Gavin Zhang, Bihong Beth Chen, Huiyan Ma, Mahesh Botejue, Eric H. Choi, Weiwei Zhang
Author Affiliations +
Abstract

Purpose

The influential holistic processing hypothesis attributes expertise in medical image perception to cognitive processing of global gist information. However, it has remained unclear whether or how experts use rapid global impression of images for their subsequent diagnostic decisions based on the focal sign of cancer. We hypothesized that continuous-global and discrete-local processes jointly attribute to radiological experts’ detection of mammogram, with different weights and temporal dynamics.

Approach

We examined experienced versus inexperienced observers’ performance at first (500 ms) versus second (2500 ms) mammogram image presentation in an abnormality detection task. We applied a dual-trace signal detection (DTSD) model of receiver operating characteristic (ROC) to assess the time-varying contributions of global and focal cancer signals on mammogram reading and medical expertise.

Results

The hierarchical Bayesian DTSD modeling of empirical ROCs revealed that mammogram expertise (experienced versus inexperienced observers) manifests largely in a continuous-global component for the detection of the gist of abnormality at the early phase of mammogram reading. For the second presentation of the same mammogram images, the experienced participants showed increased task performance that was largely driven by better processing of discrete-local information, whereas the global processing of abnormality remained saturated from the first exposure. Modeling of the mouse trajectory of the confidence rating responses further revealed the temporal dynamics of global and focal processing.

Conclusions

These results suggest a joint contribution of continuous-global and discrete-local processes on medical expertise, and these processes could be analytically dissociated.

CC BY: © 2023 Society of Photo-Optical Instrumentation Engineers (SPIE)
Hyung-Bum Park, Lilian Azer, Shinhae Ahn, Tam-Dan Dinh, Gabriela Macias, Gavin Zhang, Bihong Beth Chen, Huiyan Ma, Mahesh Botejue, Eric H. Choi, and Weiwei Zhang "Contributions of global and local processing on medical image perception," Journal of Medical Imaging 10(S1), S11911 (8 May 2023). https://doi.org/10.1117/1.JMI.10.S1.S11911
Received: 28 December 2022; Accepted: 24 April 2023; Published: 8 May 2023
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Cited by 1 scholarly publication.
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KEYWORDS
Image processing

Mammography

Signal processing

Medical imaging

Visual process modeling

Data modeling

Signal detection

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