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From Handcrafted to Deep-Learning-Based Cancer Radiomics: Challenges and Opportunities

https://doi.org/10.1109/msp.2019.2900993

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Outgoing claims: the papers this work cites, builds on, or argues with.

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What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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inferred← citeshttps://doi.org/10.1016/j.bspc.2021.103246openalex-snapshot

Sperm morphology analysis by using the fusion of two-stage fine-tuned deep networks

inferred← citeshttps://doi.org/10.1016/j.canrad.2020.04.009openalex-snapshot

Radiological assessment after stereotactic body radiation of lung tumours

inferred← citeshttps://doi.org/10.1016/j.cmpb.2021.106018openalex-snapshot

Semi-supervised GAN-based Radiomics Model for Data Augmentation in Breast Ultrasound Mass Classification

inferred← citeshttps://doi.org/10.1016/j.cmpb.2022.106906openalex-snapshot

Diagnosis of endometrium hyperplasia and screening of endometrial intraepithelial neoplasia in histopathological images using a global-to-local multi-scale convolutional neural network

inferred← citeshttps://doi.org/10.1016/j.cmpb.2022.106948openalex-snapshot

Deep learning based time-to-event analysis with PET, CT and joint PET/CT for head and neck cancer prognosis

inferred← citeshttps://doi.org/10.1016/j.cmpb.2023.107939openalex-snapshot

Deep learning-based outcome prediction using PET/CT and automatically predicted probability maps of primary tumor in patients with oropharyngeal cancer

inferred← citeshttps://doi.org/10.1016/j.cmpb.2026.109500openalex-snapshot

FSCL-BC: Federated supervised contrastive learning for breast cancer diagnosis with high sensitivity

inferred← citeshttps://doi.org/10.1016/j.compbiomed.2020.103629openalex-snapshot

Deep learning-based segmentation of breast masses in dedicated breast CT imaging: Radiomic feature stability between radiologists and artificial intelligence

inferred← citeshttps://doi.org/10.1016/j.compbiomed.2021.104400openalex-snapshot

The impact of the variation of imaging parameters on the robustness of Computed Tomography radiomic features: A review

inferred← citeshttps://doi.org/10.1016/j.compbiomed.2021.105161openalex-snapshot

Deep Residual Separable Convolutional Neural Network for lung tumor segmentation

inferred← citeshttps://doi.org/10.1016/j.compbiomed.2023.106896openalex-snapshot

A deep learning-based cancer survival time classifier for small datasets

inferred← citeshttps://doi.org/10.1016/j.compbiomed.2024.109140openalex-snapshot

radMLBench: A dataset collection for benchmarking in radiomics

inferred← citeshttps://doi.org/10.1016/j.compbiomed.2025.110491openalex-snapshot

Radiomics and deep learning characterisation of liver malignancies in CT images – A systematic review

inferred← citeshttps://doi.org/10.1016/j.cpet.2021.09.010openalex-snapshot

AI-Based Detection, Classification and Prediction/Prognosis in Medical Imaging

inferred← citeshttps://doi.org/10.1016/j.cpet.2023.05.002openalex-snapshot

AI-Enhanced PET and MR Imaging for Patients with Breast Cancer

inferred← citeshttps://doi.org/10.1016/j.crad.2025.106926openalex-snapshot

Radiomics for lung cancer diagnosis, management, and future prospects

inferred← citeshttps://doi.org/10.1016/j.critrevonc.2025.105040openalex-snapshot

Explainable artificial intelligence for multi-modal cancer analysis: From genomics to immunology

inferred← citeshttps://doi.org/10.1016/j.csbj.2023.11.040openalex-snapshot

Cluster-based radiomics reveal spatial heterogeneity of bevacizumab response for treatment of radiotherapy-induced cerebral necrosis

inferred← citeshttps://doi.org/10.1016/j.displa.2025.103032openalex-snapshot

Machine learning for anterior cruciate ligament and meniscus analysis in knee MRI: A comprehensive review

inferred← citeshttps://doi.org/10.1016/j.ebiom.2024.105311openalex-snapshot

Multiregional dynamic contrast-enhanced MRI-based integrated system for predicting pathological complete response of axillary lymph node to neoadjuvant chemotherapy in breast cancer: multicentre study

inferred← citeshttps://doi.org/10.1016/j.ejca.2023.02.017openalex-snapshot

CT radiomics compared to a clinical model for predicting checkpoint inhibitor treatment outcomes in patients with advanced melanoma

inferred← citeshttps://doi.org/10.1016/j.ejmp.2021.03.008openalex-snapshot

The promise of artificial intelligence and deep learning in PET and SPECT imaging

inferred← citeshttps://doi.org/10.1016/j.ejrad.2024.111744openalex-snapshot

Non-traumatic brachial plexopathy identification from routine MRIs: Retrospective studies with deep learning networks

inferred← citeshttps://doi.org/10.1016/j.ejrad.2024.111811openalex-snapshot

Early prediction of radiotherapy outcomes in pharyngeal cancer using deep learning on baseline [18F]Fluorodeoxyglucose positron emission Tomography/Computed tomography

inferred← citeshttps://doi.org/10.1016/j.ejro.2026.100808openalex-snapshot

Performance of MRI-based deep learning models in differentiation of triple negative breast cancer from other breast cancer subtypes: A systematic review and meta-analysis

inferred← citeshttps://doi.org/10.1016/j.engappai.2024.109972openalex-snapshot

Application of deep learning-based multimodal fusion technology in cancer diagnosis: A survey

inferred← citeshttps://doi.org/10.1016/j.eswa.2020.113501openalex-snapshot

Deep learning radiomics in breast cancer with different modalities: Overview and future

inferred← citeshttps://doi.org/10.1016/j.heliyon.2023.e14371openalex-snapshot

A pathomic approach for tumor-infiltrating lymphocytes classification on breast cancer digital pathology images

inferred← citeshttps://doi.org/10.1016/j.ijrobp.2023.12.032openalex-snapshot

Exploring Deep Learning for Estimating the Isoeffective Dose of FLASH Irradiation From Mouse Intestinal Histological Images

inferred← citeshttps://doi.org/10.1016/j.imed.2021.05.003openalex-snapshot

Predicting the pathological status of mammographic microcalcifications through a radiomics approach

inferred← citeshttps://doi.org/10.1016/j.iotech.2021.100028openalex-snapshot

Radiomics in immuno-oncology

inferred← citeshttps://doi.org/10.1016/j.ipm.2022.103046openalex-snapshot

Differential diagnosis of hepatocellular carcinoma and hepatic hemangioma based on maximum wavelet-coefficient statistics: Novel radiomics features from plain CT

inferred← citeshttps://doi.org/10.1016/j.isci.2023.106527openalex-snapshot

Deep learning radiomics-based preoperative prediction of recurrence in chronic rhinosinusitis

inferred← citeshttps://doi.org/10.1016/j.jbo.2026.100753openalex-snapshot

From imaging to omics: deep learning is bridging MRI and liquid biopsy in bone tumor diagnosis

inferred← citeshttps://doi.org/10.1016/j.jmir.2025.102023openalex-snapshot

Explainable artificial intelligence for pneumonia classification: Clinical insights into deformable prototypical part network in pediatric chest x-ray images

inferred← citeshttps://doi.org/10.1016/j.jrras.2023.100679openalex-snapshot

The study of ultrasonography based on deep learning in breast cancer

inferred← citeshttps://doi.org/10.1016/j.mcpdig.2025.100253openalex-snapshot

Deep Learning Applications in Clinical Cancer Detection: A Review of Implementation Challenges and Solutions

inferred← citeshttps://doi.org/10.1016/j.mri.2021.12.008openalex-snapshot

MRI-based peritumoral radiomics analysis for preoperative prediction of lymph node metastasis in early-stage cervical cancer: A multi-center study

inferred← citeshttps://doi.org/10.1016/j.neucom.2025.131192openalex-snapshot

Advancements in radiomics: A comprehensive survey of feature types and their correlation on modalities and regions

inferred← citeshttps://doi.org/10.1016/j.neuroimage.2023.120229openalex-snapshot

A novel collaborative self-supervised learning method for radiomic data

inferred← citeshttps://doi.org/10.1016/j.oraloncology.2023.106460openalex-snapshot

Spatially-aware clustering improves AJCC-8 risk stratification performance in oropharyngeal carcinomas

inferred← citeshttps://doi.org/10.1016/j.patcog.2021.107942openalex-snapshot

MIXCAPS: A capsule network-based mixture of experts for lung nodule malignancy prediction

inferred← citeshttps://doi.org/10.1016/j.patrec.2020.09.010openalex-snapshot

COVID-CAPS: A capsule network-based framework for identification of COVID-19 cases from X-ray images

inferred← citeshttps://doi.org/10.1016/j.pdpdt.2025.104528openalex-snapshot

Artificial intelligence and different image modalities in uveal melanoma diagnosis and prognosis: A narrative review

inferred← citeshttps://doi.org/10.1016/j.radonc.2022.06.010openalex-snapshot

CT-based radiomics nomogram may predict local recurrence-free survival in esophageal cancer patients receiving definitive chemoradiation or radiotherapy: A multicenter study

inferred← citeshttps://doi.org/10.1016/j.radonc.2025.111121openalex-snapshot

Dosiomics-guided deep learning for radiation esophagitis prediction in lung cancer: optimal region of interest definition via multi-branch fusion auxiliary learning

inferred← citeshttps://doi.org/10.1016/j.rcl.2023.02.006openalex-snapshot

Radiomics and Radiogenomics of Ovarian Cancer

inferred← citeshttps://doi.org/10.1016/j.semcancer.2020.04.002openalex-snapshot

Radiomics in breast cancer classification and prediction

inferred← citeshttps://doi.org/10.1016/j.tranon.2023.101719openalex-snapshot

Deep radiomic model based on the sphere–shell partition for predicting treatment response to chemotherapy in lung cancer

inferred← citeshttps://doi.org/10.1016/j.wneu.2020.11.113openalex-snapshot

Meningioma Consistency Can Be Defined by Combining the Radiomic Features of Magnetic Resonance Imaging and Ultrasound Elastography. A Pilot Study Using Machine Learning Classifiers

inferred← citeshttps://doi.org/10.1016/j.xops.2026.101252openalex-snapshot

Deep Learning and Radiomics Assessment for Highly Myopic Glaucoma Detection Based on Fundus Photography

inferred← citeshttps://doi.org/10.1016/j.ymeth.2020.07.003openalex-snapshot

Reinventing radiation therapy with machine learning and imaging bio-markers (radiomics): State-of-the-art, challenges and perspectives

inferred← citeshttps://doi.org/10.1016/j.zemedi.2026.04.004openalex-snapshot

Applications of artificial intelligence in nuclear medicine

inferred← citeshttps://doi.org/10.1038/s41374-021-00692-5openalex-snapshot

Predicting 1p/19q co-deletion status from magnetic resonance imaging using deep learning in adult-type diffuse lower-grade gliomas: a discovery and validation study

inferred← citeshttps://doi.org/10.1038/s41467-025-63812-5openalex-snapshot

Development of deep learning-based narrow-band imaging endocytoscopic classification for predicting colorectal lesions from a retrospective study

inferred← citeshttps://doi.org/10.1038/s41571-022-00707-0openalex-snapshot

Criteria for the translation of radiomics into clinically useful tests

inferred← citeshttps://doi.org/10.1038/s41571-025-01067-1openalex-snapshot

Radiomics Quality Score 2.0: towards radiomics readiness levels and clinical translation for personalized medicine

inferred← citeshttps://doi.org/10.1038/s41597-026-06781-8openalex-snapshot

RadRepro CBCT: An Open-Access CBCT Phantom Dataset for Improved Standardization and Reproducibility of Radiomics Research

inferred← citeshttps://doi.org/10.1038/s41598-020-64824-5openalex-snapshot

3D-MCN: A 3D Multi-scale Capsule Network for Lung Nodule Malignancy Prediction

inferred← citeshttps://doi.org/10.1038/s41598-020-69106-8openalex-snapshot

$$\text {DRTOP}$$: deep learning-based radiomics for the time-to-event outcome prediction in lung cancer

inferred← citeshttps://doi.org/10.1038/s41598-023-34653-3openalex-snapshot

Cluster analysis of autoencoder-extracted FDG PET/CT features identifies multiple myeloma patients with poor prognosis

inferred← citeshttps://doi.org/10.1038/s41598-023-45983-7openalex-snapshot

Dual adversarial deconfounding autoencoder for joint batch-effects removal from multi-center and multi-scanner radiomics data

inferred← citeshttps://doi.org/10.1038/s41598-024-51630-6openalex-snapshot

Deep learning–radiomics integrated noninvasive detection of epidermal growth factor receptor mutations in non-small cell lung cancer patients

inferred← citeshttps://doi.org/10.1038/s41598-024-53491-5openalex-snapshot

The effect of data resampling methods in radiomics

inferred← citeshttps://doi.org/10.1038/s41598-024-69870-xopenalex-snapshot

Beyond hand-crafted features for pretherapeutic molecular status identification of pediatric low-grade gliomas

inferred← citeshttps://doi.org/10.1038/s41598-024-77498-0openalex-snapshot

Multi-task Bayesian model combining FDG-PET/CT imaging and clinical data for interpretable high-grade prostate cancer prognosis

inferred← citeshttps://doi.org/10.1038/s41598-024-81188-2openalex-snapshot

Deep learning on CT scans to predict checkpoint inhibitor treatment outcomes in advanced melanoma

inferred← citeshttps://doi.org/10.1038/s41598-026-46244-zopenalex-snapshot

FedLiverNet: a federated learning framework for privacy-preserving and efficient liver cancer detection

inferred← citeshttps://doi.org/10.1055/s-0039-3400268openalex-snapshot

Quantification in Musculoskeletal Imaging Using Computational Analysis and Machine Learning: Segmentation and Radiomics

inferred← citeshttps://doi.org/10.1063/5.0117655openalex-snapshot

Chest CT images analysis with deep learning algorithms for COVID-19 diagnostic for Iraqi center

inferred← citeshttps://doi.org/10.1088/1361-6560/ac3d17openalex-snapshot

Predicting distant metastases in soft-tissue sarcomas from PET-CT scans using constrained hierarchical multi-modality feature learning

inferred← citeshttps://doi.org/10.1088/1361-6560/ac60b9openalex-snapshot

The stability of oncologic MRI radiomic features and the potential role of deep learning: a review

inferred← citeshttps://doi.org/10.1088/1361-6560/ac678aopenalex-snapshot

Towards a safe and efficient clinical implementation of machine learning in radiation oncology by exploring model interpretability, explainability and data-model dependency

inferred← citeshttps://doi.org/10.1088/1361-6560/ac6fabopenalex-snapshot

Radiomics-guided radiation therapy: opportunities and challenges

inferred← citeshttps://doi.org/10.1088/1361-6560/ac7fd7openalex-snapshot

Impact of image quality on radiomics applications

inferred← citeshttps://doi.org/10.1088/1361-6560/aca388openalex-snapshot

Radiomics in clinical trials: perspectives on standardization

inferred← citeshttps://doi.org/10.1088/1361-6560/ae36e0openalex-snapshot

The long and winding road of radiomics: learnings from two meta-analyses of the radiomics quality score

inferred← citeshttps://doi.org/10.1093/bjro/tzae038openalex-snapshot

Application of CT-based foundational artificial intelligence and radiomics models for prediction of survival for lung cancer patients treated on the NRG/RTOG 0617 clinical trial

inferred← citeshttps://doi.org/10.1093/noajnl/vdaf100openalex-snapshot

Radiomics based on MRI and 18F-FDG PET/CT predicts response to EGFR-TKI therapy based on primary NSCLC and brain metastasis

inferred← citeshttps://doi.org/10.1097/mnm.0000000000001543openalex-snapshot

Radiomics: a quantitative imaging biomarker in precision oncology

inferred← citeshttps://doi.org/10.1097/ms9.0000000000001412openalex-snapshot

Predictive value and potential association of PET/CT radiomics on lymph node metastasis of cervical cancer

inferred← citeshttps://doi.org/10.1097/rct.0000000000001502openalex-snapshot

Radiomic Signatures Based on Mammography and Magnetic Resonance Imaging as New Markers for Estimation of Ki-67 and HER-2 Status in Breast Cancer

inferred← citeshttps://doi.org/10.1097/rct.0000000000001584openalex-snapshot

Prognostic Value of a Combined Nomogram Model Integrating 3-Dimensional Deep Learning and Radiomics for Head and Neck Cancer

inferred← citeshttps://doi.org/10.1101/2022.12.19.22283574openalex-snapshot

CT radiomics to predict checkpoint inhibitors treatment outcomes in patients with advanced cutaneous melanoma

inferred← citeshttps://doi.org/10.1101/2023.07.25.23293133openalex-snapshot

Deep learning on CT scans to predict checkpoint inhibitor treatment outcomes in advanced melanoma

inferred← citeshttps://doi.org/10.1101/2024.03.26.24304839openalex-snapshot

Ultrasonic Texture Analysis for Acute Myocardial Infarction Risk Stratification: A Pilot Study

inferred← citeshttps://doi.org/10.1101/2024.05.13.24307241openalex-snapshot

Predicting local control of brain metastases after stereotactic radiotherapy with clinical, radiomics and deep learning features

inferred← citeshttps://doi.org/10.1101/2025.06.13.25329594openalex-snapshot

Predicting overall survival of NSCLC patients with clinical, radiomics and deep learning features

inferred← citeshttps://doi.org/10.1109/access.2023.3281546openalex-snapshot

Gated Deep Reinforcement Learning With Red Deer Optimization for Medical Image Classification

inferred← citeshttps://doi.org/10.1109/access.2024.3430983openalex-snapshot

Decision-Level Fusion Classification of Ovarian CT Benign and Malignant Tumors Based on Radiomics and Deep Learning of Dual Views

inferred← citeshttps://doi.org/10.1109/aqtr61889.2024.10554139openalex-snapshot

Pancreatic Tumor Recognition from CT Images through Advanced Deep Learning Techniques

inferred← citeshttps://doi.org/10.1109/bhi67747.2025.11269564openalex-snapshot

Radiomics Initialized Deep Embedding Network (RIDE-Net) to Prognosticate Survival in Renal Cancers

inferred← citeshttps://doi.org/10.1109/bibm55620.2022.9995030openalex-snapshot

MVSF: Multi-View Signature Fusion Network for Noninvasively Predicting Ki67 Status

inferred← citeshttps://doi.org/10.1109/ccict65753.2025.00071openalex-snapshot

Enhanced Detection of Gastric Cancer in Endoscopic Images Using Advanced Deep Convolutional Neural Networks with Custom Architectures

inferred← citeshttps://doi.org/10.1109/cibcb.2019.8791473openalex-snapshot

Integrating deep and radiomics features in cancer bioimaging

inferred← citeshttps://doi.org/10.1109/cis-ram61939.2024.10673062openalex-snapshot

CMIB: A Cross Modal Interaction with Information Bottleneck Framework for Multimodal Survival Analysis

inferred← citeshttps://doi.org/10.1109/embc44109.2020.9175922openalex-snapshot

BoostCaps: A Boosted Capsule Network for Brain Tumor Classification

inferred← citeshttps://doi.org/10.1109/embc58623.2025.11252958openalex-snapshot

Symptomatic and Asymptomatic Carotid Plaques Classification using CT Images and Hybrid Deep Transfer Learning

inferred← citeshttps://doi.org/10.1109/healthcom56612.2023.10472397openalex-snapshot

Pre-Trained Tabular Transformer for Real-Time, Efficient, Stable Radiomics Data Processing: A Comprehensive Study

inferred← citeshttps://doi.org/10.1109/i4tech55392.2022.9952993openalex-snapshot

GECC-Net: Gene Expression-Based Cancer Classification using Hybrid Fuzzy Ranking Network with Multi-kernel SVM

inferred← citeshttps://doi.org/10.1109/icassp40776.2020.9053243openalex-snapshot

MDR-SURV: A Multi-Scale Deep Learning-Based Radiomics for Survival Prediction in Pulmonary Malignancies

inferred← citeshttps://doi.org/10.1109/icesic67389.2026.11496485openalex-snapshot

Hybrid Deep Learning-Based Multi-Class Brain Stroke Classification Using CT Imaging with Optimized Feature Learning

inferred← citeshttps://doi.org/10.1109/icftic59930.2023.10455886openalex-snapshot

MVHRL: Multi-view Hierarchical Representation Learning for Subtype Classification of Non-small Cell Lung Cancer

inferred← citeshttps://doi.org/10.1109/icip.2019.8803615openalex-snapshot

Capsule Networks’ Interpretability for Brain Tumor Classification Via Radiomics Analyses

inferred← citeshttps://doi.org/10.1109/icip51287.2024.10648264openalex-snapshot

Nyctale: Neuro-Evidence Transformer for Adaptive and Personalized Lung Nodule Invasiveness Prediction

inferred← citeshttps://doi.org/10.1109/icssas57918.2023.10331672openalex-snapshot

Comparative Analysis of Machine Learning Models for Early Prediction of Cancer

inferred← citeshttps://doi.org/10.1109/icssit46314.2019.8987580openalex-snapshot

Proposing an Early Diagnostic Deep Learning Approach to Detect Lung Cancer from Short-Breaths

inferred← citeshttps://doi.org/10.1109/ictacs56270.2022.9988410openalex-snapshot

Feature Extraction and Analysis of Prostate Cancer MR Images

inferred← citeshttps://doi.org/10.1109/igarss55030.2025.11244029openalex-snapshot

Kolmogorov–Arnold Networks for High-Resolution Range Profile Recognition In Radar Applications

inferred← citeshttps://doi.org/10.1109/iscmi67495.2025.11358572openalex-snapshot

Benchmarking Machine Learning Classifiers for Breast Cancer Detection Using Consensus Radiomic Features

inferred← citeshttps://doi.org/10.1109/jbhi.2022.3181791openalex-snapshot

DeepMTS: Deep Multi-Task Learning for Survival Prediction in Patients With Advanced Nasopharyngeal Carcinoma Using Pretreatment PET/CT

inferred← citeshttps://doi.org/10.1109/jbhi.2022.3192010openalex-snapshot

Reconstruction-Assisted Feature Encoding Network for Histologic Subtype Classification of Non-Small Cell Lung Cancer

inferred← citeshttps://doi.org/10.1109/jtehm.2021.3108390openalex-snapshot

Radiomics Based Bayesian Inversion Method for Prediction of Cancer and Pathological Stage

inferred← citeshttps://doi.org/10.1109/jtehm.2022.3219625openalex-snapshot

A Self-Attention-Guided 3D Deep Residual Network With Big Transfer to Predict Local Failure in Brain Metastasis After Radiotherapy Using Multi-Channel MRI

inferred← citeshttps://doi.org/10.1109/lsp.2020.3034858openalex-snapshot

BayesCap: A Bayesian Approach to Brain Tumor Classification Using Capsule Networks

inferred← citeshttps://doi.org/10.1109/msp.2021.3090674openalex-snapshot

Diagnosis/Prognosis of COVID-19 Chest Images via Machine Learning and Hypersignal Processing: Challenges, opportunities, and applications

inferred← citeshttps://doi.org/10.1109/prai53619.2021.9551095openalex-snapshot

Improved Convolutional Neural Multi-Resolution Wavelet Network for COVID-19 Pneumonia Classification

inferred← citeshttps://doi.org/10.1109/tai.2025.3597580openalex-snapshot

PipeMamba: State Space Model for Efficient Video-Based Sewer Defect Classification

inferred← citeshttps://doi.org/10.1109/tase.2026.3670430openalex-snapshot

PipeCLIP: Defect-Conditioned and Cross-Focus-Driven Vision-Language Model for Video-Based Sewer Defect Inspection

inferred← citeshttps://doi.org/10.1109/tce.2026.3678618openalex-snapshot

Debiased Driver State Recognition via Irrelevant Context and Social Bias Removal for Vision-Language Model in Reproducing Kernel Hilbert Spaces

inferred← citeshttps://doi.org/10.1109/tcsvt.2024.3433415openalex-snapshot

TMFF: Trustworthy Multi-Focus Fusion Framework for Multi-Label Sewer Defect Classification in Sewer Inspection Videos

inferred← citeshttps://doi.org/10.1109/tits.2025.3542447openalex-snapshot

Trustworthy Driver State Perception via Contextual Interaction-Driven Evidential Vision-Language Fusion in Vehicular Cyber-Physical Systems

inferred← citeshttps://doi.org/10.1109/trpms.2023.3291848openalex-snapshot

Radiomics and Machine Learning for Skeletal Muscle Injury Recovery Prediction

inferred← citeshttps://doi.org/10.1109/tsp55681.2022.9851353openalex-snapshot

A Shallow Convolution Neural Network for Predicting Lung Cancer Through Analysis of Histopathological Tissue Images

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