{"product_id":"data-engineering-in-medical-imaging-9783032080080","title":"Data Engineering in Medical Imaging","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e\u003cp\u003e.- Surgical Vision World Model.\u003cbr\u003e.- Overcoming Data Scarcity: Brain Tumor Segmentation in Pediatric and African Populations.\u003cbr\u003e.- PiMPiC: An Overlap-Aware Contrastive Learning Framework for 3D Patch-Based Medical Image Segmentation.\u003cbr\u003e.- DiffusionXRay: A Diffusion and GAN-Based Approach for Enhancing Digitally Reconstructed Chest Radiographs.\u003cbr\u003e.- SingleStrip: learning skull-stripping from a single labeled example.\u003cbr\u003e.- Kvasir-VQA-x1: A Multimodal Dataset for Medical Reasoning and Robust MedVQA in Gastrointestinal Endoscopy.\u003cbr\u003e.- Do Edges Matter? Investigating Edge-Enhanced Pre-Training for Medical Image Segmentation.\u003cbr\u003e.- Enhancing Malaria-Infected Red Blood Cell Detection with Domain-Aware Generative Augmentation.\u003cbr\u003e.- Analysis of Transferability Estimation Metrics for Surgical Phase Recognition.\u003cbr\u003e.- Expert-Guided Explainable Few-Shot Learning for Medical Image Diagnosis.\u003cbr\u003e.- Lesion-Aware Visual-Language Fusion for Automated Image Captioning of Ulcerative Colitis Endoscopic Examinations.\u003cbr\u003e.- Zero-shot Monocular Metric Depth for Endoscopic Images.\u003cbr\u003e.- Robust Federated Anomaly Detection Using Dual-Signal Autoencoders: Application to Kidney Stone Identification in Ureteroscopy.\u003cbr\u003e.- RadSURF: Automated Synthesis of Radiographs and Surface Representation of Vertebrae for Single View Reconstruction.\u003cbr\u003e.- A Dataset and Benchmark for Enhancing Retained Foreign Object Detection Through Physics-based Image Synthesis.\u003cbr\u003e.- Unmasking Interstitial Lung Diseases: Leveraging Masked Autoencoders for Diagnosis.\u003cbr\u003e.- Robust Early Detection of Barrett’s Neoplasia: Addressing Low-Prevalence Challenges with Generative Modeling.\u003cbr\u003e.- Instance-Balanced Patch Sampling for Whole-Body Lesion Segmentation.\u003cbr\u003e.- Calibrated Self-supervised Vision Transformers Improve Intracranial Arterial Calcification Segmentation from Clinical CT Head Scans.\u003cbr\u003e.- Estimating 2D Keypoints of Surgical Tools Using Vision-Language Models with Low-Rank Adaptation.\u003cbr\u003e.- Exploring Pre-training Across Domains for Few-Shot Surgical Skill Assessment.\u003cbr\u003e.- Effect of Data Augmentation on Conformal Prediction for Diabetic Retinopathy.\u003cbr\u003e.- Addressing Bias in VLMs for Glaucoma Detection Without Protected Attribute Supervision.\u003cbr\u003e.- Balancing Redundancy and Diversity: An In-Depth Analysis of Active Learning for Laparoscopic Video Segmentation\u003cstrong\u003e.\u003c\/strong\u003e\u003c\/p\u003e","brand":"Springer","offers":[{"title":"Default Title","offer_id":52151402168663,"sku":"9783032080080","price":76.49,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9783032080080.jpg?v=1762961080","url":"https:\/\/bookcurl.com\/products\/data-engineering-in-medical-imaging-9783032080080","provider":"Book Curl","version":"1.0","type":"link"}