AIMC Topic: Lipoma

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Preoperative Contrast-Enhanced CT-Based Deep Learning Radiomics Model for Distinguishing Retroperitoneal Lipomas and Well‑Differentiated Liposarcomas.

Academic radiology Jul 14, 2024
RATIONALE AND OBJECTIVES: To assess the efficacy of a preoperative contrast-enhanced CT (CECT)-based deep learning radiomics nomogram (DLRN) for predicting murine double minute 2 (MDM2) gene amplification as a means of distinguishing between retroper...
Preoperative Care Lipoma Nomograms Contrast Media Liposarcoma Retroperitoneal Neoplasms Diagnosis, Differential Middle Aged Deep Learning Radiomics Male Retrospective Studies Tomography, X-Ray Computed Aged Adult Female Humans
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Robotic resection of a lipoma in the deep lesser pelvis - a video vignette.

Colorectal disease : the official journal of the Association of Coloproctology of Great Britain and Ireland Mar 27, 2023
Lipoma Lesser Pelvis Humans Pelvis Robotics Rectal Neoplasms Robotic Surgical Procedures
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Simultaneous excision of pelvic lipoma and robot-assisted radical prostatectomy.

BMJ case reports Mar 27, 2023
Lipoma is a benign mesenchymal tumour that can develop in any part of the body containing adipose tissue. Very few cases of pelvic lipomas have been reported in the literature. Due to their location and slow growth, pelvic lipomas are often asymptoma...
Humans Male Prostatic Neoplasms Lipoma Robotic Surgical Procedures Prostate Robotics Prostatectomy
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Prediction of lipomatous soft tissue malignancy on MRI: comparison between machine learning applied to radiomics and deep learning.

European radiology experimental Sep 8, 2022
OBJECTIVES: Malignancy of lipomatous soft-tissue tumours diagnosis is suspected on magnetic resonance imaging (MRI) and requires a biopsy. The aim of this study is to compare the performances of MRI radiomic machine learning (ML) analysis with deep l...
Magnetic Resonance Imaging Humans Lipoma Soft Tissue Neoplasms Machine Learning Neoplasms, Adipose Tissue Deep Learning
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Novel computer aided diagnostic models on multimodality medical images to differentiate well differentiated liposarcomas from lipomas approached by deep learning methods.

Orphanet journal of rare diseases Apr 7, 2022
BACKGROUND: Deep learning methods have great potential to predict tumor characterization, such as histological diagnosis and genetic aberration. The objective of this study was to evaluate and validate the predictive performance of multimodality imag...
Cohort Studies Liposarcoma Retrospective Studies Lipoma Humans Deep Learning Algorithms
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Machine learning based diagnostics of veterinary cancer on ultrasound and optical imaging data.

The veterinary quarterly Dec 1, 2025
Study advances current diagnostic efficiency of canine/feline (sub-)cutaneous tumors using machine learning and multimodal imaging data. White light (WL), fluorescence (FL) and ultrasound (US) imaging were combined into hybrid approaches to different...
Dog Diseases Sarcoma Support Vector Machine Dogs Optical Imaging Lipoma Mastocytoma Animals Cats Cat Diseases Ultrasonography Machine Learning
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Differentiation of canine and feline neoplasms using multi-modal imaging and machine learning.

Scientific reports May 27, 2025
Canine/feline (sub-)cutaneous tumors, which include lipomas, mastocytomas and soft tissue sarcomas, introduce diagnostic challenges due to inherent tissue heterogeneity, accompanied by diverse clinical pathogenesis. Current study integrates conventio...
Machine Learning Animals Multimodal Imaging Diagnosis, Differential Dogs Ultrasonography Support Vector Machine Lipoma Mastocytoma Cats Cat Diseases Dog Diseases Sarcoma
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