Search Results - "Mohinta, Samia"

Computational limits to the legibility of the imaged human brain by Ruffle, James K., Gray, Robert J, Mohinta, Samia, Pombo, Guilherme, Kaul, Chaitanya, Hyare, Harpreet, Rees, Geraint, Nachev, Parashkev

“…•Individuals remain poorly predictable from population-level analyses of the brain.•The fidelity limits data scale, compute, and model flexibility impose are…”
Get full text

DEMOGRAPHICS, GENETICS, AND EPIGENETICS INflUENCE THE LESION DISTRIBUTION OF GLIOMA by Ruffle, James, Mohinta, Samia, Brandner, Sebastian, Hyare, Harpreet, Nachev, Parashkev

“…Abstract AIMS Tumour heterogeneity is increasingly recognized as a major obstacle to therapeutic innovation in neuro- oncology. Gliomas typically exhibit a…”
Get full text

NIMG-35. THE DEEP TOPOLOGY OF GLIOMAS by Ruffle, James, Mohinta, Samia, Brandner, Sebastian, Hyare, Harpreet, Nachev, Parashkev

“…Abstract Tumor heterogeneity is increasingly recognized as a major obstacle to therapeutic innovation in neuro-oncology. Gliomas typically exhibit a spectrum…”
Get full text

Identifying Enhancing Tumour Without Contrast-Enhanced Imaging by Ruffle, James, Mohinta, Samia, Gray, Robert, Hyare, Harpreet, Nachev, Parashkev

“…Abstract AIMS Brain tumours are heterogenous entities comprising multiple broad tissue sub-types when imaged with MRI. Delineating the enhancing tumour…”
Get full text

Deep Learning for Tumour Segmentation with Missing Data by Ruffle, James, Mohinta, Samia, Gray, Robert, Hyare, Harpreet, Nachev, Parashkev

“…Abstract AIMS Brain tumour segmentation remains a challenging task, complicated by the marked heterogeneity of imaging appearances and their distribution…”
Get full text

AUTOMATED VASARI FEATURE SET REPORTING FOR GLIOMAS IS EffCIENT AND EFFECTIVE by Lee, Faith, Ruffle, James, Mohinta, Samia, Kopanitsa, Valeria, Nachev, Parashkev, Hyare, Harpreet

“…Abstract AIMS The quantitative evaluation of gliomas using the VASARI MRI feature sets aims to facilitate consistent radiological reporting of gliomas but…”
Get full text

Brain tumour genetic network signatures of survival by Ruffle, James K, Mohinta, Samia, Pombo, Guilherme, Gray, Robert, Kopanitsa, Valeriya, Lee, Faith, Brandner, Sebastian, Hyare, Harpreet, Nachev, Parashkev

“…Abstract Tumour heterogeneity is increasingly recognized as a major obstacle to therapeutic success across neuro-oncology. Gliomas are characterized by…”
Get full text

BRAIN TUMOUR GENETIC NETWORK SIGNATURES SUPERIORLY FORECAST SURVIVAL by Ruffle, James, Mohinta, Samia, Pombo, Guilherme, Gray, Robert, Kopanitsa, Valeriya, Lee, Faith, Brandner, Sebastian, Hyare, Harpreet, Nachev, Parashkev

“…Abstract AIMS Gliomas typically exhibit a spectrum of genetic mutations, reflecting multiple, potentially complex interactions across distinct molecular…”
Get full text

CNSC-26. NETWORK SIGNATURES OF SURVIVAL IN BRAIN TUMOUR GENETICS by Ruffle, James, Mohinta, Samia, Pombo, Guilherme, Gray, Robert, Kopanitsa, Valeriya, Lee, Faith, Brandner, Sebastian, Hyare, Harpreet, Nachev, Parashkev

“…Abstract Tumor heterogeneity is increasingly recognized as a major obstacle to therapeutic innovation across neuro-oncology. Gliomas typically exhibit a…”
Get full text

VASARI-auto: Equitable, efficient, and economical featurisation of glioma MRI by Ruffle, James K., Mohinta, Samia, Baruteau, Kelly Pegoretti, Rajiah, Rebekah, Lee, Faith, Brandner, Sebastian, Nachev, Parashkev, Hyare, Harpreet

“…[Display omitted] •We present VASARI-auto, an automated featurisation software for glioma.•Lesion segmentation performance was compatible with the current…”
Get full text

Brain tumour segmentation with incomplete imaging data by Ruffle, James K, Mohinta, Samia, Gray, Robert, Hyare, Harpreet, Nachev, Parashkev

“…Abstract Progress in neuro-oncology is increasingly recognized to be obstructed by the marked heterogeneity—genetic, pathological, and clinical—of brain…”
Get full text

MODELLING GBM RECURRENCE: THE INflUENCE OF PERI-LESIONAL OEDEMA AND THE DISCONNECTOME by Tariq, Ms Manaal, Ruffle, Dr James, Mohinta, Ms Samia, Brothwell, Dr Morag, Brandner, Prof Sebastian, Nachev, Prof Parashkev, Hyare, Harpreet

“…Abstract AIMS Residual tumour burden after surgery in GBM patients is a prognostic imaging biomarker, often involving the area of T2 signal elevation…”
Get full text

MATHEMATICAL MODELLING OF SURVIVAL IN LOW GRADE GLIOMAS AT MALIGNANT TRANSFORMATION WITH XGBOOST by Tan, Ms Lily, Ruffle, Dr James, Mohinta, Ms Samia, Rees, Dr Jeremy, Brandner, Prof Sebastian, Nachev, Prof Parashkev, Hyare, Dr Harpeet

“…Abstract AIMS To develop non-linear machine learning models using the XGBoost algorithm to predict a continuous (overall survival (OS) and a binary survival…”
Get full text

VASARI-AUTO: PERFORMANT, EQUITABLE, EffiCIENT, ECONOMIC, AND SURVIVAL PREDICTIVE FEATURISATION OF GLIOMA MRI by Ruffle, Dr James, Mohinta, Ms Samia, Baruteau, Dr Kelly Pegoretti, Rajiah, Dr Rebekah, Lee, Ms Faith, Brandner, Prof Sebastian, Nachev, Prof Parashkev, Hyare, Dr Harpreet

“…Abstract AIMS The VASARI (Visually AcceSAble Rembrandt Images) MRI feature set is a quantitative system designed to standardize glioma imaging descriptions…”
Get full text

VASARI-auto: equitable, efficient, and economical featurisation of glioma MRI by Ruffle, James K, Mohinta, Samia, Baruteau, Kelly Pegoretti, Rajiah, Rebekah, Lee, Faith, Brandner, Sebastian, Nachev, Parashkev, Hyare, Harpreet

“…The VASARI MRI feature set is a quantitative system designed to standardise glioma imaging descriptions. Though effective, deriving VASARI is time-consuming…”
Get full text

Computational limits to the legibility of the imaged human brain by Ruffle, James K, Gray, Robert J, Mohinta, Samia, Pombo, Guilherme, Kaul, Chaitanya, Hyare, Harpreet, Rees, Geraint, Nachev, Parashkev

“…Our knowledge of the organisation of the human brain at the population-level is yet to translate into power to predict functional differences at the…”
Get full text

Brain tumour segmentation with incomplete imaging data by Ruffle, James K, Mohinta, Samia, Gray, Robert J, Hyare, Harpreet, Nachev, Parashkev

“…The complex heterogeneity of brain tumours is increasingly recognized to demand data of magnitudes and richness only fully-inclusive, large-scale collections…”
Get full text

Brain tumour genetic network signatures of survival by Ruffle, James K, Mohinta, Samia, Pombo, Guilherme, Gray, Robert, Kopanitsa, Valeriya, Lee, Faith, Brandner, Sebastian, Hyare, Harpreet, Nachev, Parashkev

“…Tumour heterogeneity is increasingly recognized as a major obstacle to therapeutic success across neuro-oncology. Gliomas are characterised by distinct…”
Get full text