Datadriven Bröstradiologi – Fredrik Strands forskargrupp

Publikationer

Utvalda publikationer

• Article: EUROPEAN RADIOLOGY. 2024;34(8):5415-5424

  Reader bias in breast cancer screening related to cancer prevalence and artificial intelligence decision support-a reader study

  Al-Bazzaz H; Janicijevic M; Strand F
• Article: LANCET DIGITAL HEALTH. 2023;5(10):e703-e711

  Artificial intelligence for breast cancer detection in screening mammography in Sweden: a prospective, population-based, paired-reader, non-inferiority study

  Dembrower K; Crippa A; Colon E; Eklund M
• Review: RADIOLOGY. 2023;307(5):e222639

  Standalone AI for Breast Cancer Detection at Screening Digital Mammography and Digital Breast Tomosynthesis:A Systematic Review and Meta-Analysis

  Yoon JH; Strand F; Baltzer PAT; Conant EF; Gilbert FJ; Lehman CD; Morris EA; Mullen LA; Nishikawa RM; Sharma N; Vejborg I; Moy L; Mann RM
• Article: JOURNAL OF MEDICAL IMAGING. 2023;10(Suppl 2):S22405

  Implications for downstream workload based on calibrating an artificial intelligence detection algorithm by standalone-reader or combined-reader sensitivity matching

  Dembrower K; Salim M; Eklund M; Lindholm P; Strand F
• Article: JOURNAL OF MEDICAL IMAGING. 2023;10(6):061404

  VAI-B: a multicenter platform for the external validation of artificial intelligence algorithms in breast imaging

  Cossio F; Schurz H; Engstrom M; Barck-Holst C; Tsirikoglou A; Lundstrom C; Gustafsson H; Smith K; Zackrisson S; Strand F
• Conference publication: 2023 IEEE/CVF WINTER CONFERENCE ON APPLICATIONS OF COMPUTER VISION (WACV). 2023;:3942-3951

  PatchDropout: Economizing Vision Transformers Using Patch Dropout

  Liu Y; Matsoukas C; Strand F; Azizpour H; Smith K
• Article: NATURE MEDICINE. 2022;28(1):136-143

  Optimizing risk-based breast cancer screening policies with reinforcement learning

  Yala A; Mikhael PG; Lehman C; Lin GG; Strand F; Wan Y-L; Hughes K; Satuluru S; Kim T; Banerjee I; Gichoya J; Trivedi H; Barzilay R
• Article: RADIOLOGY. 2021;301(2):295-308

  Breast MRI during Neoadjuvant Chemotherapy: Lack of Background Parenchymal Enhancement Suppression and Inferior Treatment Response

  Onishi N; Li W; Newitt DC; Harnish RJ; Strand F; Nguyen AA-T; Arasu VA; Gibbs J; Jones EF; Wilmes LJ; Kornak J; Joe BN; Price ER; Ojeda-Fournier H
• Article: SCIENCE TRANSLATIONAL MEDICINE. 2021;13(578):eaba4373

  Toward robust mammography-based models for breast cancer risk

  Yala A; Mikhael PG; Strand F; Lin G; Smith K; Wan Y-L; Lamb L; Hughes K; Lehman C; Barzilay R
• Article: ACTA RADIOLOGICA. 2020;61(12):1600-1607

  The association between breast cancer risk factors and background parenchymal enhancement at dynamic contrast-enhanced breast MRI

  Hellgren R; Saracco A; Strand F; Eriksson M; Sundbom A; Hall P; Dickman PW
• Article: NPJ BREAST CANCER. 2020;6(1):63

  Predicting breast cancer response to neoadjuvant treatment using multi-feature MRI: results from the I-SPY 2 TRIAL

  Li W; Newitt DC; Gibbs J; Wilmes LJ; Jones EF; Arasu VA; Strand F; Onishi N; Nguyen AA-T; Kornak J; Joe BN; Price ER; Ojeda-Fournier H; Eghtedari M; Zamora KW; Woodard SA; Umphrey H; Bernreuter W; Nelson M; Church AL; Bolan P; Kuritza T; Ward K; Morley K; Wolverton D; Fountain K; Lopez-Paniagua D; Hardesty L; Brandt K; McDonald ES; Rosen M; Kontos D; Abe H; Sheth D; Crane EP; Dillis C; Sheth P; Hovanessian-Larsen L; Bang DH; Porter B; Oh KY; Jafarian N; Tudorica A; Niell BL; Drukteinis J; Newell MS; Cohen MA; Giurescu M; Berman E; Lehman C; Partridge SC; Fitzpatrick KA; Borders MH; Yang WT; Dogan B; Goudreau S; Chenevert T; Yau C; DeMichele A; Berry D; Esserman LJ; Hylton NM
• Article: JAMA ONCOLOGY. 2020;6(10):1581-1588

  External Evaluation of 3 Commercial Artificial Intelligence Algorithms for Independent Assessment of Screening Mammograms

  Salim M; Wahlin E; Dembrower K; Azavedo E; Foukakis T; Liu Y; Smith K; Eklund M; Strand F
• Article: RADIOLOGY. 2020;297(1):33-39

  Range of Radiologist Performance in a Population-based Screening Cohort of 1 Million Digital Mammography Examinations

  Salim M; Dembrower K; Eklund M; Lindholm P; Strand F
• Article: LANCET DIGITAL HEALTH. 2020;2(9):e468-e474

  Effect of artificial intelligence-based triaging of breast cancer screening mammograms on cancer detection and radiologist workload: a retrospective simulation study

  Dembrower K; Wahlin E; Liu Y; Salim M; Smith K; Lindholm P; Eklund M; Strand F
• Article: JOURNAL OF DIGITAL IMAGING. 2020;33(2):408-413

  A Multi-million Mammography Image Dataset and Population-Based Screening Cohort for the Training and Evaluation of Deep Neural Networks-the Cohort of Screen-Aged Women (CSAW)

  Dembrower K; Lindholm P; Strand F
• Conference publication: CANCER RESEARCH. 2020;80(4):pd9-06-pd9-06

  Additive benefit of MRI background parenchymal enhancement (BPE) to an MRI tumor volume model for predicting pathologic complete response (pCR) to neoadjuvant treatment in ISPY2

  Arasu VA; Kim P; Li W; Strand F; McHargue C; Jones E; Newitt D; Kornak J; Esserman L; Hylton N
• Article: RADIOLOGY. 2020;294(2):265-272

  Comparison of a Deep Learning Risk Score and Standard Mammographic Density Score for Breast Cancer Risk Prediction

  Dembrower K; Liu Y; Azizpour H; Eklund M; Smith K; Lindholm P; Strand F
• Book chapter: MEDICAL IMAGE COMPUTING AND COMPUTER ASSISTED INTERVENTION – MICCAI 2020: LECTURE NOTES IN COMPUTER SCIENCE. 2020;p. 230-240

  Decoupling Inherent Risk and Early Cancer Signs in Image-Based Breast Cancer Risk Models

  Liu Y; Azizpour H; Strand F; Smith K
• Article: BREAST CANCER RESEARCH. 2018;20(1):31

  Long-term prognostic implications of risk factors associated with tumor size: a case study of women regularly attending screening

  Strand F; Humphreys K; Holm J; Eriksson M; Tornberg S; Hall P; Azavedo E; Czene K

Alla gruppmedlemmars publikationer

• Journal article: JOURNAL OF MEDICAL IMAGING. 2025;12(Suppl 2):s22014

  Simulating dynamic tumor contrast enhancement in breast MRI using conditional generative adversarial networks.

  Osuala R; Joshi S; Tsirikoglou A; Garrucho L; Pinaya WHL; Lang DM; Schnabel JA; Diaz O; Lekadir K
• Article: NPJ DIGITAL MEDICINE. 2025;8(1):259

  Simulating mismatch between calibration and target population in AI for mammography the retrospective VAIB study

  Schurz H; Solander K; Astrom D; Cossio F; Choi T; Dustler M; Lundstrom C; Gustafsson H; Zackrisson S; Strand F
• Journal article: EUROPEAN JOURNAL OF RADIOLOGY. 2025;186:112062

  Patient experience and healthcare cost aspects of vacuum-assisted excision of breast lesions. A report from the Swedish VAE randomized clinical trial.

  Zouzos A; Fredriksson I; Karakatsanis A; Foukakis T; Strand F
• Article: EUROPEAN JOURNAL OF RADIOLOGY. 2025;186:112062

  Patient experience and healthcare cost aspects of vacuum-assisted excision of breast lesions. A report from the Swedish VAE randomized clinical trial

  Zouzos A; Fredriksson I; Karakatsanis A; Foukakis T; Strand F
• Doctoral thesis: 2025

  Benign breast lesions : analysis by artificial intelligence and removal by vacuum-assisted excision

  Zouzos A
• Article: SCIENTIFIC DATA. 2025;12(1):453

  A large-scale multicenter breast cancer DCE-MRI benchmark dataset with expert segmentations

  Garrucho L; Kushibar K; Reidel C-A; Joshi S; Osuala R; Tsirikoglou A; Bobowicz M; del Riego J; Catanese A; Gwozdziewicz K; Cosaka M-L; Abo-Elhoda PM; Tantawy SW; Sakrana SS; Shawky-Abdelfatah NO; Salem AMA; Kozana A; Divjak E; Ivanac G; Nikiforaki K; Klontzas ME; Garcia-Dosda R; Gulsun-Akpinar M; Lafci O; Mann R; Martin-Isla C; Prior F; Marias K; Starmans MPA; Strand F; Diaz O; Igual L; Lekadir K
• Article: RADIOLOGY. 2025;314(3):e242566

  Human-AI Interaction in the ScreenTrustCAD Trial: Recall Proportion and Positive Predictive Value Related to Screening Mammograms Flagged by AI CAD versus a Human Reader

  Dembrower KE; Crippa A; Eklund M; Strand F
• Article: EUROPEAN JOURNAL OF RADIOLOGY. 2025;183:111895

  Effect of needle size on outcomes of vacuum-assisted excision of breast lesions. A randomized controlled trial

  Zouzos A; Fredriksson I; Karakatsanis A; Aristokleous I; Foukakis T; Strand F
• Review: JAPANESE JOURNAL OF RADIOLOGY. 2025;43(6):927-933

  AI image analysis as the basis for risk-stratified screening

  Strand F
• Article: MEDICAL IMAGE ANALYSIS. 2025;99:103320

  Mammography classification with multi-view deep learning techniques: and transformer-based architectures

  Manigrasso F; Milazzo R; Russo AS; Lamberti F; Strand F; Pagnani A; Morra L
• Article: EJSO. 2025;51(1):109368

  Prospective evaluation of MRI artefacts following breast conserving surgery and sentinel lymph node dissection with the magnetic technique

  Jazrawi A; Pantiora E; Abdsaleh S; Ng CL; Zouzos A; Gagliardi T; Warnberg F; Eriksson S; Karakatsanis A
• Preprint: ARXIV. 2024

  Artificial Intelligence-Informed Handheld Breast Ultrasound for Screening: A Systematic Review of Diagnostic Test Accuracy

  Bunnell A; Valdez D; Strand F; Glaser Y; Sadowski P; Shepherd JA
• Article: EJSO. 2024;50(11):108624

  Magseed application for detecting recurrent lymph node metastasis in papillary thyroid cancer: A novel minimally invasive Approach

  Shabo I; Zouzos A; Fredholm H; Branstrom R; Hoog A; Kjellman M; Ihre-Lundgren C
• Preprint: ARXIV. 2024

  Random Token Fusion for Multi-View Medical Diagnosis

  Guo J; Matsoukas C; Strand F; Smith K
• Article: MEDICAL DECISION MAKING. 2024;44(7):828-842

  Modeling Radiologists' Assessments to Explore Pairing Strategies for Optimized Double Reading of Screening Mammograms

  Gommers JJJ; Abbey CK; Strand F; Taylor-Phillips S; Jenkinson DJ; Larsen M; Hofvind S; Broeders MJM; Sechopoulos I
• Article: NATURE MEDICINE. 2024;30(9):2623-2630

  AI-based selection of individuals for supplemental MRI in population-based breast cancer screening: the randomized ScreenTrustMRI trial

  Salim M; Liu Y; Sorkhei M; Ntoula D; Foukakis T; Fredriksson I; Wang Y; Eklund M; Azizpour H; Smith K; Strand F
• Journal article: 3D PRINTING IN MEDICINE. 2024;10(1):27

  3D-printing inherently MRI-visible accessories in aiding MRI-guided biopsies

  Wang Y
• Article: EUROPEAN RADIOLOGY. 2024;34(8):5415-5424

  Reader bias in breast cancer screening related to cancer prevalence and artificial intelligence decision support-a reader study

  Al-Bazzaz H; Janicijevic M; Strand F
• Preprint: ARXIV. 2024

  A large-scale multicenter breast cancer DCE-MRI benchmark dataset with expert segmentations

  Garrucho L; Kushibar K; Reidel C-A; Joshi S; Osuala R; Tsirikoglou A; Bobowicz M; del Riego J; Catanese A; Gwoździewicz K; Cosaka M-L; Abo-Elhoda PM; Tantawy SW; Sakrana SS; Shawky-Abdelfatah NO; Abdo-Salem AM; Kozana A; Divjak E; Ivanac G; Nikiforaki K; Klontzas ME; García-Dosdá R; Gulsun-Akpinar M; Lafcı O; Mann R; Martín-Isla C; Prior F; Marias K; Starmans MPA; Strand F; Díaz O; Igual L; Lekadir K
• Conference publication: PROCEEDINGS OF SPIE - THE INTERNATIONAL SOCIETY FOR OPTICAL ENGINEERING. 2024;13174:131741g-131741g-6-64

  AI lesion risk score at different exposure settings

  Tingberg A; Dahlblom V; Bakic P; Schurz H; Strand F; Zackrisson S; Dustler M
• Journal article: CANCER RESEARCH. 2024;84(9_Supplement):po4-07-03-po4-07-03

  Abstract PO4-07-03: Machine learning breast cancer risk prediction using sequential past mammograms - a pilot study

  Leong L; Xu M; Huang W; Zhang E; Loh E; Teo SY; Lim GH; Tan VKM; Sim Y; Strand F; Tan R
• Article: RADIOLOGY. 2024;311(1):e232535

  Use of an AI Score Combining Cancer Signs, Masking, and Risk to Select Patients for Supplemental Breast Cancer Screening

  Liu Y; Sorkhei M; Dembrower K; Azizpour H; Strand F; Smith K
• Journal article: CANCER RESEARCH. 2024;84(6_Supplement):3449

  Abstract 3449: Is AI-enhanced breast ultrasound ready for breast cancer screening in low-resource environments? A systematic review

  Bunnell A; Valdez D; Strand F; Glaser Y; Sadowski P; Shepherd JA
• Article: BMJ OPEN. 2024;14(2):e084014

  Women's perceptions and attitudes towards the use of AI in mammography in Sweden: a qualitative interview study

  Johansson JV; Dembrower K; Strand F; Grauman A
• Book chapter: MEDICAL IMAGE COMPUTING AND COMPUTER ASSISTED INTERVENTION – MICCAI 2024: LECTURE NOTES IN COMPUTER SCIENCE. 2024;p. 757-767

  Towards Rapid Mycetoma Species Diagnosis: A Deep Learning Approach for Stain-Invariant Classification on H&E Images from Senegal

  Zinsou KMS; Diop CT; Diop I; Tsirikoglou A; Siddig EE; Sow D; Ndiaye M
• Article: BRITISH JOURNAL OF RADIOLOGY. 2023;96(1151):20230210

  Differences and similarities in false interpretations by AI CAD and radiologists in screening mammography

  Salim M; Dembrower K; Eklund M; Smith K; Strand F
• Article: RADIOLOGY. 2023;309(1):e222691

  Optimizing the Pairs of Radiologists That Double Read Screening Mammograms

  Gommers JJJ; Abbey CK; Strand F; Taylor-Phillips S; Jenkinson DJ; Larsen M; Hofvind S; Sechopoulos I; Broeders MJM
• Article: LANCET DIGITAL HEALTH. 2023;5(10):e703-e711

  Artificial intelligence for breast cancer detection in screening mammography in Sweden: a prospective, population-based, paired-reader, non-inferiority study

  Dembrower K; Crippa A; Colon E; Eklund M
• Article: JMIR AI. 2023;2:e48123

  Effect of Benign Biopsy Findings on an Artificial Intelligence-Based Cancer Detector in Screening Mammography: Retrospective Case-Control Study

  Zouzos A; Milovanovic A; Dembrower K; Strand F
• Article: LAKARTIDNINGEN. 2023;120:23065

  Så kan AI valideras för klinisk implementering.

  Strand F; Zackrisson S; Gustafsson H
• Review: RADIOLOGY. 2023;307(5):e222639

  Standalone AI for Breast Cancer Detection at Screening Digital Mammography and Digital Breast Tomosynthesis:A Systematic Review and Meta-Analysis

  Yoon JH; Strand F; Baltzer PAT; Conant EF; Gilbert FJ; Lehman CD; Morris EA; Mullen LA; Nishikawa RM; Sharma N; Vejborg I; Moy L; Mann RM
• Doctoral thesis: 2023

  Deep learning algorithms for tumor detection in screening mammography

  Salim M
• Preprint: JMIR PREPRINTS. 2023

  Effect of Benign Biopsy Findings on an Artificial Intelligence–Based Cancer Detector in Screening Mammography: Retrospective Case-Control Study (Preprint)

  Zouzos A; Milovanovic A; Dembrower K; Strand F
• Article: JOURNAL OF MEDICAL IMAGING. 2023;10(Suppl 2):S22405

  Implications for downstream workload based on calibrating an artificial intelligence detection algorithm by standalone-reader or combined-reader sensitivity matching

  Dembrower K; Salim M; Eklund M; Lindholm P; Strand F
• Article: JOURNAL OF MEDICAL IMAGING. 2023;10(6):061404

  VAI-B: a multicenter platform for the external validation of artificial intelligence algorithms in breast imaging

  Cossio F; Schurz H; Engstrom M; Barck-Holst C; Tsirikoglou A; Lundstrom C; Gustafsson H; Smith K; Zackrisson S; Strand F
• Article: JOURNAL OF THE NATIONAL COMPREHENSIVE CANCER NETWORK. 2023;21(2):143-152.e4

  Factors Associated With False-Positive Recalls in Mammography Screening

  Mao X; He W; Humphreys K; Eriksson M; Holowko N; Strand F; Hall P; Czene K
• Conference publication: 2023 IEEE/CVF WINTER CONFERENCE ON APPLICATIONS OF COMPUTER VISION (WACV). 2023;:3942-3951

  PatchDropout: Economizing Vision Transformers Using Patch Dropout

  Liu Y; Matsoukas C; Strand F; Azizpour H; Smith K
• Preprint: MEDRXIV. 2022

  Benign biopsy effect on artificial intelligence cancer detector in screening mammography – a retrospective study

  Zouzos A; Molovanovic A; Dembrower K; Strand F
• Review: JAMA NETWORK OPEN. 2022;5(12):e2244212

  Yield of Surveillance Imaging After Mastectomy With or Without Reconstruction for Patients With Prior Breast Cancer A Systematic Review and Meta-analysis

  Smith D; Sepehr S; Karakatsanis A; Strand F; Valachis A
• Preprint: ARXIV. 2022

  High-resolution synthesis of high-density breast mammograms: Application to improved fairness in deep learning based mass detection

  Garrucho L; Kushibar K; Osuala R; Diaz O; Catanese A; del Riego J; Bobowicz M; Strand F; Igual L; Lekadir K
• Preprint: ARXIV. 2022

  PatchDropout: Economizing Vision Transformers Using Patch Dropout

  Liu Y; Matsoukas C; Strand F; Azizpour H; Smith K
• Article: JOURNAL OF CLINICAL ONCOLOGY. 2022;40(16):1732-1740

  Multi-Institutional Validation of a Mammography-Based Breast Cancer Risk Model

  Yala A; Mikhael PG; Strand F; Lin G; Satuluru S; Kim T; Banerjee I; Gichoya J; Trivedi H; Lehman CD; Hughes K; Sheedy DJ; Matthis LM; Karunakaran B; Hegarty KE; Sabino S; Silva TB; Evangelista MC; Caron RF; Souza B; Mauad EC; Patalon T; Handelman-Gotlib S; Guindy M; Barzilay R
• Article: BREAST CANCER RESEARCH AND TREATMENT. 2022;193(3):589-595

  False-negative rate in the extended prospective TATTOO trial evaluating targeted axillary dissection by carbon tattooing in clinically node-positive breast cancer patients receiving neoadjuvant systemic therapy

  de Boniface J; Frisell J; Kuehn T; Wiklander-Brakenhielm I; Dembrower K; Nyman P; Zouzos A; Gerber B; Reimer T; Hartmann S
• Doctoral thesis: 2022

  Deep learning in breast cancer screening

  Dembrower K
• Journal article: LINKÖPING STUDIES IN SCIENCE AND TECHNOLOGY DISSERTATIONS. 2022;2202

  Synthetic data for visual machine learning : A data-centric approach

  Tsirikoglou A
• Article: FRONTIERS IN ONCOLOGY. 2022;12:1044496

  High-resolution synthesis of high-density breast mammograms: Application to improved fairness in deep learning based mass detection

  Garrucho L; Kushibar K; Osuala R; Diaz O; Catanese A; del Riego J; Bobowicz M; Strand F; Igual L; Lekadir K
• Article: NATURE MEDICINE. 2022;28(1):136-143

  Optimizing risk-based breast cancer screening policies with reinforcement learning

  Yala A; Mikhael PG; Lehman C; Lin GG; Strand F; Wan Y-L; Hughes K; Satuluru S; Kim T; Banerjee I; Gichoya J; Trivedi H; Barzilay R
• Preprint: ARXIV. 2021

  CSAW-M: An Ordinal Classification Dataset for Benchmarking Mammographic Masking of Cancer

  Sorkhei M; Liu Y; Azizpour H; Azavedo E; Dembrower K; Ntoula D; Zouzos A; Strand F; Smith K
• Editorial comment: JOURNAL OF THE AMERICAN COLLEGE OF RADIOLOGY. 2021;18(11):1564-1565

  A Call for Controlled Validation Data Sets: Promoting the Safe Introduction of Artificial Intelligence in Breast Imaging

  Strand F; Patel BK; Allen B
• Article: RADIOLOGY. 2021;301(2):295-308

  Breast MRI during Neoadjuvant Chemotherapy: Lack of Background Parenchymal Enhancement Suppression and Inferior Treatment Response

  Onishi N; Li W; Newitt DC; Harnish RJ; Strand F; Nguyen AA-T; Arasu VA; Gibbs J; Jones EF; Wilmes LJ; Kornak J; Joe BN; Price ER; Ojeda-Fournier H
• Corrigendum: BMC NEPHROLOGY. 2021;22(1):326

  Negative effects of iodine-based contrast agent on renal function in patients with moderate reduced renal function hospitalized for COVID-19 (vol 22, 297, 2021)

  Kistner A; Tamm C; Svensson AM; Beckman MO; Strand F; Skold M; Nyren S
• Journal article: 2021

  Optimizing the pairs of radiologists that double read screening mammograms

  Gommers J; Abbey C; Strand F; Broeders M; Sechopoulos I
• Article: BMC NEPHROLOGY. 2021;22(1):297

  Negative effects of iodine-based contrast agent on renal function in patients with moderate reduced renal function hospitalized for COVID-19

  Kistner A; Tamm C; Svensson AM; Beckman MO; Strand F; Skold M; Nyren S
• Preprint: RESEARCH SQUARE. 2021

  Optimizing risk-based breast cancer screening policies with reinforcement learning

  Yala A; Mikhael P; Lehman C; Lin G; Strand F; Wang Y-L; Hughes K; Satuluru S; Kim T; Banerjee I; Gichoya J; Trivedi H; Barzilay R
• Preprint: 2021

  Ensembles of GANs for synthetic training data generation

  Eilertsen G; Tsirikoglou A; Lundström C; Unger J
• Preprint: RESEARCH SQUARE. 2021

  Negative effects of iodine-based contrast agent on renal function in patients with moderate reduced renal function hospitalized for Covid-19

  Tamm C; Svensson AM; Beckman M; Strand F; Sköld M; Nyrén S; Kistner A
• Article: SCIENCE TRANSLATIONAL MEDICINE. 2021;13(578):eaba4373

  Toward robust mammography-based models for breast cancer risk

  Yala A; Mikhael PG; Strand F; Lin G; Smith K; Wan Y-L; Lamb L; Hughes K; Lehman C; Barzilay R
• Book chapter: MEDICAL IMAGE COMPUTING AND COMPUTER ASSISTED INTERVENTION – MICCAI 2021: LECTURE NOTES IN COMPUTER SCIENCE. 2021;p. 624-633

  Primary Tumor and Inter-Organ Augmentations for Supervised Lymph Node Colon Adenocarcinoma Metastasis Detection

  Tsirikoglou A; Stacke K; Eilertsen G; Unger J
• Article: FRONTIERS IN MEDICINE. 2021;8:666723

  Widespread Parenchymal Abnormalities and Pulmonary Embolism on Contrast-Enhanced CT Predict Disease Severity and Mortality in Hospitalized COVID-19 Patients

  Jalde FC; Beckman MO; Svensson AM; Bell M; Skold M; Strand F; Nyren S; Kistner A
• Preprint: ARXIV. 2020

  Development and evaluation of a 3D annotation software for interactive COVID-19 lesion segmentation in chest CT

  Bendazzoli S; Brusini I; Astaraki M; Persson M; Yu J; Connolly B; Nyrén S; Strand F; Smedby Ö; Wang C
• Article: ACTA RADIOLOGICA. 2020;61(12):1600-1607

  The association between breast cancer risk factors and background parenchymal enhancement at dynamic contrast-enhanced breast MRI

  Hellgren R; Saracco A; Strand F; Eriksson M; Sundbom A; Hall P; Dickman PW
• Article: NPJ BREAST CANCER. 2020;6(1):63

  Predicting breast cancer response to neoadjuvant treatment using multi-feature MRI: results from the I-SPY 2 TRIAL

  Li W; Newitt DC; Gibbs J; Wilmes LJ; Jones EF; Arasu VA; Strand F; Onishi N; Nguyen AA-T; Kornak J; Joe BN; Price ER; Ojeda-Fournier H; Eghtedari M; Zamora KW; Woodard SA; Umphrey H; Bernreuter W; Nelson M; Church AL; Bolan P; Kuritza T; Ward K; Morley K; Wolverton D; Fountain K; Lopez-Paniagua D; Hardesty L; Brandt K; McDonald ES; Rosen M; Kontos D; Abe H; Sheth D; Crane EP; Dillis C; Sheth P; Hovanessian-Larsen L; Bang DH; Porter B; Oh KY; Jafarian N; Tudorica A; Niell BL; Drukteinis J; Newell MS; Cohen MA; Giurescu M; Berman E; Lehman C; Partridge SC; Fitzpatrick KA; Borders MH; Yang WT; Dogan B; Goudreau S; Chenevert T; Yau C; DeMichele A; Berry D; Esserman LJ; Hylton NM
• Article: RADIOLOGY. 2020;297(2):327-333

  Identification of Women at High Risk of Breast Cancer Who Need Supplemental Screening

  Eriksson M; Czene K; Strand F; Zackrisson S; Lindholm P; Lang K; Fornvik D; Sartor H; Mavaddat N; Easton D; Hall P
• Article: JAMA ONCOLOGY. 2020;6(10):1581-1588

  External Evaluation of 3 Commercial Artificial Intelligence Algorithms for Independent Assessment of Screening Mammograms

  Salim M; Wahlin E; Dembrower K; Azavedo E; Foukakis T; Liu Y; Smith K; Eklund M; Strand F
• Article: RADIOLOGY. 2020;297(1):33-39

  Range of Radiologist Performance in a Population-based Screening Cohort of 1 Million Digital Mammography Examinations

  Salim M; Dembrower K; Eklund M; Lindholm P; Strand F
• Article: COMPUTER GRAPHICS FORUM. 2020;39(6):426-451

  A Survey of Image Synthesis Methods for Visual Machine Learning

  Tsirikoglou A; Eilertsen G; Unger J
• Article: LANCET DIGITAL HEALTH. 2020;2(9):e468-e474

  Effect of artificial intelligence-based triaging of breast cancer screening mammograms on cancer detection and radiologist workload: a retrospective simulation study

  Dembrower K; Wahlin E; Liu Y; Salim M; Smith K; Lindholm P; Eklund M; Strand F
• Article: JOURNAL OF BREAST IMAGING. 2020;2(4):352-360

  Predictive Value of Breast MRI Background Parenchymal Enhancement for Neoadjuvant Treatment Response among HER2-Patients

  Arasu VA; Kim P; Li W; Strand F; McHargue C; Harnish R; Newitt DC; Jones EF; Glymour MM; Kornak J; Esserman LJ; Hylton NM
• Preprint: ARXIV. 2020

  Adding Seemingly Uninformative Labels Helps in Low Data Regimes

  Matsoukas C; Hernandez ABI; Liu Y; Dembrower K; Miranda G; Konuk E; Haslum JF; Zouzos A; Lindholm P; Strand F; Smith K
• Preprint: ARXIV. 2020

  Decoupling Inherent Risk and Early Cancer Signs in Image-based Breast Cancer Risk Models

  Liu Y; Azizpour H; Strand F; Smith K
• Article: TOMOGRAPHY. 2020;6(2):101-110

  Comparison of Segmentation Methods in Assessing Background Parenchymal Enhancement as a Biomarker for Response to Neoadjuvant Therapy

  Nguyen AA-T; Arasu VA; Strand F; Li W; Onishi N; Gibbs J; Jones EF; Joe BN; Esserman LJ; Newitt DC; Hylton NM
• Preprint: 2020

  A Study of Deep Learning Colon Cancer Detection in Limited Data Access Scenarios

  Tsirikoglou A; Stacke K; Eilertsen G; Lindvall M; Unger J
• Article: JOURNAL OF DIGITAL IMAGING. 2020;33(2):408-413

  A Multi-million Mammography Image Dataset and Population-Based Screening Cohort for the Training and Evaluation of Deep Neural Networks-the Cohort of Screen-Aged Women (CSAW)

  Dembrower K; Lindholm P; Strand F
• Article: JAMA NETWORK OPEN. 2020;3(3):e200265

  Evaluation of Combined Artificial Intelligence and Radiologist Assessment to Interpret Screening Mammograms

  Schaffter T; Buist DSM; Lee CI; Nikulin Y; Ribli D; Guan Y; Lotter W; Jie Z; Du H; Wang S; Feng J; Feng M; Kim H-E; Albiol F; Albiol A; Morrell S; Wojna Z; Ahsen ME; Asif U; Yepes AJ; Yohanandan S; Rabinovici-Cohen S; Yi D; Hoff B; Yu T; Neto EC; Rubin DL; Lindholm P; Margolies LR; McBride RB; Rothstein JH; Sieh W; Ben-Ari R; Harrer S; Trister A; Friend S; Norman T; Sahiner B; Strand F; Guinney J; Stolovitzky G
• Conference publication: CANCER RESEARCH. 2020;80(4):pd9-06-pd9-06

  Additive benefit of MRI background parenchymal enhancement (BPE) to an MRI tumor volume model for predicting pathologic complete response (pCR) to neoadjuvant treatment in ISPY2

  Arasu VA; Kim P; Li W; Strand F; McHargue C; Jones E; Newitt D; Kornak J; Esserman L; Hylton N
• Article: RADIOLOGY. 2020;294(2):265-272

  Comparison of a Deep Learning Risk Score and Standard Mammographic Density Score for Breast Cancer Risk Prediction

  Dembrower K; Liu Y; Azizpour H; Eklund M; Smith K; Lindholm P; Strand F
• Book chapter: MEDICAL IMAGE COMPUTING AND COMPUTER ASSISTED INTERVENTION – MICCAI 2020: LECTURE NOTES IN COMPUTER SCIENCE. 2020;p. 230-240

  Decoupling Inherent Risk and Early Cancer Signs in Image-Based Breast Cancer Risk Models

  Liu Y; Azizpour H; Strand F; Smith K
• Article: ACTA RADIOLOGICA OPEN. 2019;8(12):2058460119880315

  The future of breast cancer screening: what do participants in a breast cancer screening program think about automation using artificial intelligence?

  Jonmarker O; Strand F; Brandberg Y; Lindholm P
• Article: BREAST. 2019;46:58-63

  Breast cancer imaging - A rapidly evolving discipline

  Strand F; Zackrisson S
• Article: MEDICAL PHYSICS. 2019;46(3):1309-1316

  Derived mammographic masking measures based on simulated lesions predict the risk of interval cancer after controlling for known risk factors: a case-case analysis

  Hinton B; Ma L; Mahmoudzadeh AP; Malkov S; Fan B; Greenwood H; Joe B; Lee V; Strand F; Kerlikowske K; Shepherd J
• Article: BMC MEDICINE. 2019;17(1):24

  Discontinuation of adjuvant hormone therapy among breast cancer patients not previously attending mammography screening

  He W; Eriksson L; Tornberg S; Strand F; Hall P; Czene K
• Article: BREAST CANCER RESEARCH. 2019;21(1):8

  Localized mammographic density is associated with interval cancer and large breast cancer: a nested case-control study

  Strand F; Azavedo E; Hellgren R; Humphreys K; Eriksson M; Shepherd J; Hall P; Czene K
• Journal article: NEUROIMAGE-CLINICAL. 2019;24:101981

  Stroke atlas of the brain: Voxel-wise density-based clustering of infarct lesions topographic distribution

  Wang Y; Juliano JM; Liew S-L; McKinney AM; Payabvash S
• Article: NEUROIMAGE-CLINICAL. 2019;21:101604

  Juvenile myoclonic epilepsy has hyper dynamic functional connectivity in the dorsolateral frontal cortex

  Wang Y; Berglund IS; Uppman M; Li T-Q
• Doctoral thesis: 2018

  Determinants of interval cancer and tumor size among breast cancer screening participants

  Strand F
• Article: BREAST CANCER RESEARCH. 2018;20(1):31

  Long-term prognostic implications of risk factors associated with tumor size: a case study of women regularly attending screening

  Strand F; Humphreys K; Holm J; Eriksson M; Tornberg S; Hall P; Azavedo E; Czene K
• Journal article: CANCER RESEARCH. 2018;78(4_Supplement):p6-08-20-p6-08-20

  Abstract P6-08-20: Non-adherers of mammography screening: Delayed surgery, early discontinuation of adjuvant hormone therapy, and worse breast cancer outcomes

  He W; Bergman L; Törnberg S; Strand F; Hall P; Czene K
• Conference publication: CANCER RESEARCH. 2018;78(4)

  Non-adherers of mammography screening: Delayed surgery, early discontinuation of adjuvant hormone therapy, and worse breast cancer outcomes

  He W; Bergman LE; Tornberg S; Strand F; Hall P; Czene K
• Preprint: 2017

  Procedural Modeling and Physically Based Rendering for Synthetic Data Generation in Automotive Applications

  Tsirikoglou A; Kronander J; Wrenninge M; Unger J
• Article: BREAST CANCER RESEARCH AND TREATMENT. 2017;163(1):103-110

  Swedish prospective multicenter trial evaluating sentinel lymph node biopsy after neoadjuvant systemic therapy in clinically node-positive breast cancer

  Zetterlund LH; Frisell J; Zouzos A; Axelsson R; Hatschek T; de Boniface J; Celebioglu F
• Review: APHASIOLOGY. 2017;31(1):122-128

  Patients with aphasia and an infarct in Wernicke's area benefit from early intensive speech and language therapy

  Dembrower KEH; von Heijne A; Laska AC; Laurencikas E
• Article: INTERNATIONAL JOURNAL OF CANCER. 2017;140(1):34-40

  Longitudinal fluctuation in mammographic percent density differentiates between interval and screen-detected breast cancer.

  Strand F; Humphreys K; Eriksson M; Li J; Andersson TML; Törnberg S; Azavedo E; Shepherd J; Hall P; Czene K
• Article: BREAST CANCER RESEARCH. 2016;10(1):100

  Novel mammographic image features differentiate between interval and screen-detected breast cancer: a case-case study

  Strand F; Humphreys K; Cheddad A; Tornberg S; Azavedo E; Shepherd J; Hall P; Czene K
• Conference publication: 2016;:1-2

  Differential appearance editing for measured BRDFs

  Tsirikoglou A; Kronander J; Larsson P; Tongbuasirilai T; Gardner A; Unger J
• Doctoral thesis: 2015

  A tiny glimpse into the human brain using model-free analysis for resting-state fMRI data

  Wang Y
• Article: JOURNAL OF STROKE & CEREBROVASCULAR DISEASES. 2015;24(10):2348-2357

  Clopidogrel Resistance after Minor Ischemic Stroke or Transient Ischemic Attack is Associated with Radiological Cerebral Small-Vessel Disease

  Lundstrom A; Wallen H; von Arbin M; Jorneskog G; Gigante B; Dembrower KH; Laurencikas E; Laska AC
• Conference publication: JOURNAL OF THROMBOSIS AND HAEMOSTASIS. 2015;13:699

  Clopidogrel resistance after minor ischemic stroke or TIA is associated to pre-diabetes, hypertension and cerebral microangiopathy

  Lundstrom A; Laska AC; Gigante B; von Arbin M; Jorneskog G; Laurencikas E; Dembrower KH; Wallen H
• Article: NEUROPSYCHOLOGIA. 2008;46(11):2668-2682

  Common and unique components of inhibition and working memory: An fMRI, within-subjects investigation

  McNab F; Leroux G; Strand F; Thorell L; Bergman S; Klingberg T
• Article: BRAIN RESEARCH. 2008;1212:48-54

  Phonological working memory with auditory presentation of pseudo-words - An event related fMRI Study

  Strand F; Forssberg H; Klingberg T; Norrelgen F
• Conference publication: LIVER TRANSPLANTATION. 2004;10(6):C49

  Oral pretreatment of donors with UDCA results in an enrichment of UDCA in the portal vein and in the bile

  Strand F; Ericzon BG; Marschall HU; Källén R; Nils A; Wernersson A; Nowak G
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Medarbetare och kontakt

Gruppledare

• 

  Fredrik Strand

  Anknuten till Forskning | Docent

  E-postadress fredrik.strand@ki.se

Alla medarbetare i gruppen

• Taeyang Choi

  Forskningsingenjör

  E-postadress taeyang.choi@ki.se
• Fernando Cossio Ramirez

  Forskningsingenjör

  E-postadress fernando.cossio.ramirez@ki.se
• 

  Karin Dembrower

  Postdoktorala Studier

  E-postadress karin.dembrower@ki.se
• Jose Luis Diaz Resendiz

  Doktorand

  E-postadress jose.luis.diaz.resendiz@ki.se
• Luis Carlos Garcia Ramos

  Forskningsingenjör

  E-postadress luis.carlos.garcia.ramos@ki.se
• Shreya Jithendra

  Forskningsingenjör

  E-postadress shreya.jithendra@ki.se
• Gurwinder Kaur

  Doktorand

  E-postadress gurwinder.kaur@ki.se
• Emir Konuk

  Projektledare

  E-postadress emir.konuk@ki.se
• Lorenzo Lo Cascio

  Forskningsassistent

  E-postadress lorenzo.lo.cascio@ki.se
• 

  Mattie Salim

  Postdoktorala Studier

  E-postadress mattie.salim@ki.se
• 

  Fredrik Strand

  Anknuten till Forskning | Docent

  E-postadress fredrik.strand@ki.se
• Apostolia Tsirikoglou

  Forskningsspecialist

  E-postadress apostolia.tsirikoglou@ki.se
• 

  Yanlu Wang

  Anknuten till Forskning

  E-postadress yanlu.wang@ki.se
• 

  Athanasios Zouzos

  Anknuten till Forskning

  E-postadress athanasios.zouzos@ki.se

Besöksadress

Karolinska University Hospital, L2:03, Gävlegatan 68, Solna, 17164

Postadress

Karolinska University Hospital, L2:03, att: Fredrik Strand, Solna, 171 76, Sweden