An AI-based imaging and identification tool for diverse vector identification

Wednesday, November 16, 2022

9:12 AM – 9:24 AM PT

Location: Vancouver Convention Centre, Meeting Room 220

Presenting Author(s)

Adam Goodwin

Cofounder and CTO
VecTech LLC
Baltimore, Maryland

Co-Author(s)

Roy Faiman

Senior Scientist
National Institute of Allergy and Infectious Diseases
Rockville, Maryland
JB

Jewell Brey

R&D Engineer
VecTech LLC
Baltimore, Maryland
SP

Sanket Padmanabhan

Software Architect
VecTech LLC
Baltimore, Maryland
BM

Bala Murali Manoghar Sai Sudhakar

Software Engineer
University of Lincoln
Liverpool, England, United Kingdom
GM

Ghnana Madineni

Computer Vision Engineer
VecTech LLC
Baltimore, Maryland
TF

Tristan Ford

CEO
VecTech LLC
Baltimore, Maryland

Vector surveillance is key to assessing vector-borne disease risk management. Morphological identification of specimens by experts remains the gold standard for vector identification. Yet, only few vector management organizations have the resources for full-time medical entomologists to conduct routine identification. Many organizations rely on seasonal staff with minimal taxonomic expertise to guide important downstream intervention strategies and policy.

Applied deep learning convolutional neural networks (CNNs) for image recognition have been among the most promising technical modalities for visually differentiating between mosquito species. Parallel development includes the algorithmic ability to determine if a specimen’s species is unknown to the system. We developed these algorithms for IDX, a digital imaging system with species identification capabilities where the user images specimens and the species identification is displayed on a web dashboard within seconds. Species classification accuracy achieves 98.3 ± 0.7% over 17 mosquito species. An unknown species detection algorithm achieved a 92.7% F1-score in detecting whether a specimen was of a species known to the CNN or not for mosquito species classification.

IDX bridges the gap in vector surveillance information by equipping users with the identification capabilities of a professional entomologist and creating a standardized digital record of each specimen. Ten US organizations are currently testing IDX in the field with the goal of increasing species identification to all vectors, including ticks, both domestic and abroad.