Medical Image Classification

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Two-Stage Fine-Tuning of ResNet50 for High-Sensitivity Melanoma Detection on Dermoscopic Images
Jun 11, 2026Aryan BhagatSkin Lesion Classification Medical Image Classification
MS Computer Science, Florida Atlantic University, Boca Raton, FL
Cascade Classification of Dermoscopic Images of Skin Neoplasms with Controllable Sensitivity and External Clinical Validation
Jun 11, 2026Elena S. Kozachok, Sergey S. Seregin, Aleksandr V. Kozachok +2Skin Lesion Classification Probability Calibration
Ivannikov Institute for System Programming of the Russian Academy of Sciences (ISP RAS), Moscow, Russia · Orel Oncological Dispensary, Orel, Russia
OpenMedQ: Broad Open Pretraining for Medical Vision-Language Models
Jun 11, 2026Ibrahim Gulluk, Max Van Puyvelde, Olivier GevaertMedical VQA Medical Image Classification
Department of Electrical Engineering, Stanford University · Department of Biomedical Data Science, Stanford University School of Medicine · Department of Mathematical Modelling, Statistics and Bioinformatics, Ghent University
Multimodal Ordinal Modeling of Alzheimer's Disease Severity Using Structural MRI and Clinical Data
Jun 10, 2026Boris-Stephan Rauchmann, Jonathan Laib, Buse Ercik +2Alzheimer's Disease Medical Image Classification
Department of Neuroradiology, LMU University Hospital, Ludwig Maximilian University of Munich, Munich, Germany · Department of Psychiatry and Psychotherapy, LMU University Hospital, Ludwig Maximilian University of Munich, Munich, Germany
Intelligent Skin Cancer Detection Using a Multispectral Metasurface and a Hybrid
Jun 9, 2026Afsane Saee ArezoomandSkin Lesion Classification Medical Image Classification
Young Researchers and Elite Club, Islamic Azad University, Urmia Branch, Urmia, Iran
Multimodal Brain Tumour Classification Using Feature Fusion
Jun 9, 2026Wajih ul Islam, Muhammad Yaqoob, Javed Ali Khan +1Multimodal Classification Medical Image Classification
School of Physics, Engineering and Computer Science, University of Hertfordshire, UK
Self-Supervised Vision Transformers for CBCT-Based Detection of Temporomandibular Joint Osteoarthritis
Jun 6, 2026Shradhdha Trivedi, Vrundan Sojitra, Mariela PadillaMedical Imaging Foundation Models Cone-Beam CT
Herman Ostrow School of Dentistry, University of Southern California · Viterbi School of Engineering, University of Southern California
LLM-Guided Evolution for Medical Decision Pipelines
Jun 5, 2026Ivan Sviridov, Artem Oskin, Ivan Panin +4Clinical Triage Large Language Model-Guided Optimization
1Sber AI Lab · 2AIRI
When is 3D Worth It? A Resource-Performance Frontier for CNNs and Transformers in Lung CT
Jun 5, 2026Md Enamul Hoq, Sharafat Hossain, Imraul Emmaka +4Vision Transformer 3D Medical Imaging
Department of Biomedical Informatics, University of Arkansas for Medical Sciences · Department of Information Science, University of Arkansas at Little Rock · Department of Neuroscience, University of Arkansas for Medical Sciences
ORACLE-CT: Anatomy-Aware Support Pooling for CT Classification
Jun 3, 2026Lavsen Dahal, Yubraj Bhandari, Geoffrey Rubin +1Medical Image Classification Computed Tomography
Electrical and Computer Engineering, Pratt School of Engineering, Duke University, Durham, 27708, North Carolina, USA · Department of Mathematics, Trinity College of Arts & Sciences, Duke University, Durham, 27708, North Carolina, USA · Department of Radiology and Imaging Sciences, University of Arizona College of Medicine, Tucson, 85004 Arizona, USA +1
Deep Learning-assisted AMD Staging based on OCT and OCT Angiography
Jun 3, 2026Yukun Guo, Tristan T. Hormel, An-Lun Wu +4Medical Imaging Optical Coherence Tomography
Casey Eye Institute, Oregon Health & Science University, Portland, OR 97239, USA · Department of Biomedical Engineering, Oregon Health & Science University, Portland, OR 97239, USA · Department of Ophthalmology, Mackay Memorial Hospital, Hsinchu 300044, Taiwan
Graph-Guided Universum Learning in Generalized Eigenvalue Proximal SVMs for Alzheimer's Disease Classification
Jun 3, 2026Yogesh Kumar, Vrushank Ahire, Mudasir GanaieAlzheimer's Disease Medical Image Classification
Dept. of Computer Science and Engineering, IIT Ropar, Punjab 140001, India
Radiomic Feature Selection Using Gradient Loss of Deep Neural Network for Lung Cancer Stage Detection
Jun 3, 2026Hina Shakir, Mohammad Mohatram, Javeed Hussain +2Medical Image Classification Feature Selection
Department of Software Engineering, Bahria University, Karachi, Pakistan · Global College of Engineering and Technology, Muscat, Oman · Software Engineering & Business Incubation Center, Bahria University Karachi, Pakistan
Motion-Guided Causal Disentanglement for Robust Multi-View Cine Cardiac MRI Diagnosis
Jun 3, 2026Chuankai Xu, Cristiane De Carvalho Singulane, Mohammad Abuannadi +10Disentangled Representation Learning Causal Representation Learning
University of Virginia, Charlottesville, VA, USA · University of Chicago, Chicago, IL, USA · Ohio State University, Columbus, OH, USA +5
Effect of Demographic Bias on Skin Lesion Classification
Jun 2, 2026Ralf Raumanns, Gerard Schouten, Veronika Cheplygina +1Skin Lesion Classification Algorithmic Bias
Fontys University of Applied Science, Venlo, The Netherlands · Eindhoven University of Technology, Eindhoven, The Netherlands · IT University of Copenhagen, Denmark +1
GloResNet: A lightweight 3D CNN with global topological features for preterm brain injury prediction
Jun 1, 2026Boyu Yuan, Jiamiao Lu, Weichuan Zhang +53D Medical Imaging Medical Image Classification
Image Computing Laboratory, Shaanxi University of Science and Technology, Xi’an, China · Department of Neonatology, Shenzhen University of Advanced Technology General Hospital, Shenzhen, China · Department of Neurosurgery, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China +1
Learning Label-Efficient Interpretable Medical Image Diagnosis via Semi-supervised Hypergraph Concept Bottleneck Model
Jun 1, 2026Yijun Yang, Ruiqiang Xiao, Lijie Hu +4Concept Bottleneck Models Medical Image Classification
HKUST(GZ) · Joy Future Academy · MBZUAI +3
Bridging Topology and Deep Representation Learning: A TDA-ViT Fusion Model for Four-Class Brain Tumor Classification
May 30, 2026Faisal AhmedVision Transformer Medical Image Classification
Department of Data Science and Mathematics, Embry-Riddle Aeronautical University, 3700 Willow Creek Rd, Prescott, 86301, Arizona, USA.
3D Segment Anything Model with Visual Mamba for Diagnosing Placenta Accreta Spectrum
May 30, 2026Yuliang Zhang, Fang He, Lulu Peng +5Promptable Image Segmentation Medical Diagnosis
Department of Obstetrics and Gynecology, The Third Affiliated Hospital, Guangzhou Medical University, Guangzhou 510000, China · Department of Obstetrics, Guangzhou Women and Children’s Medical Center, Guangzhou Medical University, Guangzhou 510180, China · Department of Radiology, The Third Affiliated Hospital, Guangzhou Medical University, Guangzhou 510000, China +1
CoFiDA-M: Concept-Aware Feature Modulation for Cross-Domain Adaptation with Image-Only Inference
May 29, 2026Nurjahan Sultana, Moi Hoon Yap, Xinqi Fan +1Skin Lesion Classification Medical Image Classification
Department of Computing and Mathematics, Manchester Metropolitan University Dalton Building, Chester Street, M1 5GD Manchester, UK
Automated Prediction of Postoperative Pancreatic Fistula Using Preoperative Computed Tomography
May 29, 2026Ashok Choudhary, Chris Varghese, Leo Y. Li-Han +53D Medical Imaging Clinical Outcome Prediction
Department of Surgery, Mayo Clinic, Rochester, MN, USA · Department of Surgery, University of Auckland, Auckland, NZ · Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, MN, USA +1
Beyond Accuracy: Evaluating Efficiency, Robustness and Explainability in Deep Learning for Malaria Diagnosis
May 29, 2026Olivier Kanamugire, Kerol DjoumessiEfficient Neural Network Inference Image Corruption Robustness
African Institute for Mathematical Sciences, Kigali, Rwanda · Hertie Institute for AI in Brain Health, University of Tübingen, Germany
An Approach for Thyroid Nodule Analysis Using Thermographic Images
May 28, 2026J. R. González, É. O. Rodrigues, C. P. Damião +6Thermal Imaging Medical Image Analysis
Computer Science Department, Universidade Federal Fluminense, Av. Milton Tavares de Souzas, s/n—Boa Viagem, Niterói, RJ 24210-330, Brazil · Radiology Department, Hospital Universitário Antônio Pedro (HUAP), Av. Marquês do Paraná, 303, Niterói, RJ, Brazil · Applied Computation Group NCA-UFMA, Universidade Federal do Maranhão, Av. dos Portugueses, São Luís, 1966, MA, Brazil +2
From Kellgren-Lawrence to Calcium Pyrophosphate Crystal Deposition: A Soft-Labelling Framework for Knee Osteoarthritis Assessmen
May 27, 2026Francisco Bérchez-Moreno, Riccardo Rosati, Maria Chiara Fiorentino +6Label Distribution Learning Medical Image Classification
Departamento de Ciencia de la Computación e Inteligencia Artificial, Universidad de Córdoba, Córdoba, España · Department of Political Science, Communication, and International Relations, University of Macerata, Macerata, Italy · Department of Innovative Technologies in Medicine & Dentistry, Università degli Studi "G. D’Annunzio" Chieti - Pescara, Chieti, Italy +5
Benchmarking Ultrasound Foundation Models for Fetal Plane Classification
May 27, 2026Leya Barrientos, Yuexi Du, Nicha C. DvornekMedical Imaging Foundation Models Medical Image Classification
Radiology & Biomedical Imaging, Yale School of Medicine, USA · Department of Biomedical Engineering, Yale University, USA
Clinical Validation of the Melanoscope AI Mobile Dermoscopy Clinical Decision Support System
May 26, 2026Elena Sergeevna Kozachok, Sergey Sergeevich SereginSkin Lesion Classification Clinical Triage
1Ivannikov Institute for System Programming of the Russian Academy of Sciences (ISP RAS),2026 25 Alexander Solzhenitsyn str., Moscow, 109004, Russian Federation · 2Orel Regional Oncology Dispensary,May 2 Ippodromny lane, Orel, Russian Federation
Normal Guidance is what Attention Needs
May 26, 2026Ethan Harvey, Dennis Johan Loevlie, Michael C. HughesHealthcare 3D Medical Imaging
Department of Computer Science Tufts University
Chaos-SSL: An Attention-Based Self-Supervised Learning Framework with Chaotic Transformation for Medical Image Classification
May 26, 2026Joao Batista FlorindoContrastive Learning Data Augmentation
Institute of Mathematics, Statistics and Scientific Computing, University of Campinas, Rua Sergio Buarque de Holanda, 651, Campinas, Brazil
vSV-ViT: Variable-size SuperVertex Vision Transformer for Cortical Surface Learning in Alzheimer's Disease
May 26, 2026Geonwoo Baek, Ikbeom JangAlzheimer's Disease 3D ViTs
Department of Computer Science and Engineering, Hankuk University of Foreign Studies, Seoul, Republic of Korea
CNNs, Transformers, Hybrid, and Vision Language Models for Skin Cancer Detection
May 25, 2026Durjoy Dey, Yuhong Yan, Hassan HajjdiabHybrid CNN-Transformer Architectures Vision Transformer
Department of Computer Science and Software Engineering, Concordia University, Montreal, Canada · Ebovir Biotechnologie Inc., Montreal, Canada

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Two-Stage Fine-Tuning of ResNet50 for High-Sensitivity Melanoma Detection on Dermoscopic Images

Aryan Bhagat

MS Computer Science, Florida Atlantic University, Boca Raton, FL

Skin Lesion Classification Medical Image Classification Transfer Learning Oncology

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Melanoma is the most dangerous form of skin cancer with five-year survival rates exceeding 99% when detected early but falling sharply once the disease spreads. This paper proposes and evaluates a two-stage fine-tuning approach for ResNet50 applied to binary melanoma classification on dermoscopic images. The core challenges addressed are class imbalance and suboptimal transfer learning from single-stage fine-tuning. After stratified train/validation/test splitting, random oversampling was applied exclusively to the training set to achieve a 1:1 class balance. Stage 1 trained only the classification head with the ResNet50 base frozen, while Stage 2 fine-tuned all layers jointly at a low learning rate of 1e-5 to prevent catastrophic forgetting of learned visual features. On an independent test set of 3,826 images, the model achieved an AUC-ROC of 0.9559, accuracy of 88.34%, sensitivity of 87.56%, specificity of 89.13%, and F1-score of 88.29%. An ablation study confirms the two-stage protocol significantly outperforms single-stage fine-tuning, with sensitivity gains of over 4%. Grad-CAM visualizations demonstrate correct lesion localization. A fully deployable Streamlit detection application is provided alongside all training code.