Search Results for author: Jeremy Kawahara

Found 5 papers, 2 papers with code

Diffusion-based Data Augmentation for Skin Disease Classification: Impact Across Original Medical Datasets to Fully Synthetic Images

no code implementations12 Jan 2023 Mohamed Akrout, Bálint Gyepesi, Péter Holló, Adrienn Poór, Blága Kincső, Stephen Solis, Katrina Cirone, Jeremy Kawahara, Dekker Slade, Latif Abid, Máté Kovács, István Fazekas

Similar to recent applications of generative models, our study suggests that diffusion models are indeed effective in generating high-quality skin images that do not sacrifice the classifier performance, and can improve the augmentation of training datasets after curation.

Data Augmentation Image Generation

Skin3D: Detection and Longitudinal Tracking of Pigmented Skin Lesions in 3D Total-Body Textured Meshes

1 code implementation2 May 2021 Mengliu Zhao, Jeremy Kawahara, Kumar Abhishek, Sajjad Shamanian, Ghassan Hamarneh

Our lesion tracking algorithm achieves an average matching accuracy of 88% on a set of detected corresponding pairs of prominent lesions of subjects imaged in different poses, and an average longitudinal accuracy of 71% when encompassing additional errors due to lesion detection.

Lesion Detection

Visual Diagnosis of Dermatological Disorders: Human and Machine Performance

no code implementations4 Jun 2019 Jeremy Kawahara, Ghassan Hamarneh

Skin conditions are a global health concern, ranking the fourth highest cause of nonfatal disease burden when measured as years lost due to disability.

Lesion Classification Skin Lesion Classification

Fully Convolutional Neural Networks to Detect Clinical Dermoscopic Features

no code implementations14 Mar 2017 Jeremy Kawahara, Ghassan Hamarneh

We reformulate the task of classifying clinical dermoscopic features within superpixels as a segmentation problem, and propose a fully convolutional neural network to detect clinical dermoscopic features from dermoscopy skin lesion images.

General Classification Image Classification +2

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